Trehalose ameliorates severe acute pancreatitis by modulating gut microbial metabolism

Haibin Hao; Deren Du; Hong Lin; Lu Ke; Aikun Fu; Chongli Shi; Wei Li; Yuanzhen Li; Gaohuan Hou; Lianglan Li; Yuxiu Liu; Shengwen Shao; Weiqin Li; Zhihui Tong

doi:10.1038/s41522-026-00950-8

. 2026 Mar 6;12:81. doi: 10.1038/s41522-026-00950-8

Trehalose ameliorates severe acute pancreatitis by modulating gut microbial metabolism

Haibin Hao ^1,^#, Deren Du ^1,^#, Hong Lin ^2,^#, Lu Ke ¹, Aikun Fu ³, Chongli Shi ⁴, Wei Li ¹, Yuanzhen Li ¹, Gaohuan Hou ², Lianglan Li ¹, Yuxiu Liu ¹, Shengwen Shao ^5,^✉, Weiqin Li ^1,^2,^6,^✉, Zhihui Tong ^1,^✉

PMCID: PMC13096296 PMID: 41792152

Abstract

This study investigates the role of trehalose in modulating gut microbiota metabolism and alleviating symptoms of severe acute pancreatitis (SAP). Here, we found that gut microbial metabolism was imbalanced in SAP. In particular, we observed increased lipid metabolism and decreased carbohydrate and amino acid metabolism, which were reversed by gut microbiota depletion. Moreover, the production of trehalose was significantly increased after gut microbiota depletion. Interestingly, trehalose treatment effectively reduced pancreatic injury and ameliorated the SAP-induced microbial metabolism imbalance by promoting carbohydrate metabolism and suppressing lipid metabolism. The effect of trehalose was depend on the gut microbiota, especially the expansion of Muribaculaceae. Mechanistically, trehalose-remodelled gut microbiota suppressed SAP-induced increases in serum TG, IL-6, IL-17A, and TNF-α levels, inhibited caspase-3-mediated apoptosis, and reduced macrophage infiltration into the pancreas. Overall, our study revealed that trehalose ameliorates SAP by modulating gut microbial metabolism homeostasis, providing new insights into the “microbial metabolism‒gut‒pancreatic axis”.

Subject terms: Diseases, Gastroenterology, Microbiology

Introduction

Acute pancreatitis (AP) is a disease characterized by excessive pancreatic enzyme activation and local pancreatic inflammatory responses¹. Approximately 20–30% of patients progress to severe acute pancreatitis (SAP), which is often accompanied by multiorgan failure and infectious complications². Clinical first-line therapeutic measures are still prescribed on the basis of symptoms, and to date, there are no specific drugs available³. The prognosis and severity of AP are associated with the gut microbiota^4,5. Changes in the gut microbiota vary according to the severity of pancreatitis, and the microorganisms that are significantly altered in patients with mild, moderate, and severe AP include Bacteroides, Escherichia-Shigella, and Enterococcus, respectively⁶. Germ-free mice with AP exhibit lower inflammation than SPF mice with AP, and the depletion of gut microbes in AP model mice with broad-spectrum antibiotics attenuates pancreatic injury⁴. Therefore, the “microbiota‒gut‒pancreatic axis” is a potential drug target for treating pancreatitis.

Dietary supplementation is closely related to disease and has attracted increasing attention. Dietary supplements for enteral nutrition can reduce the incidence of systemic inflammatory response syndrome (SIRS) and organ failure in SAP patients^7,8. The addition of butyrate to the diet effectively reverses intestinal barrier damage and reduces the levels of proinflammatory cytokines induced by SAP⁹. Moreover, our previous study clinically confirmed the role of immune enhancement and enteral nutrition therapy in treating SAP^10,11. Dietary supplementation is thought to ameliorate SAP through the “microbiota‒gut‒pancreatic axis”, mainly by promoting probiotics and inhibiting harmful bacteria. Moreover, a recent study suggested that gut microbial carbohydrate metabolism regulates insulin resistance via the “microbiota‒gut‒pancreatic axis”¹². Dietary supplementation certainly affects gut microbial metabolism by modulating the gut microbiota. Therefore, studying the “microbial metabolism‒gut‒pancreatic axis”, which is affected by dietary supplementation, will improve the efficacy of SAP therapeutics.

Trehalose, which is a natural carbohydrate, is used as a dietary supplement. Trehalose has been reported to be a “sugar of life”, and it has been approved as a safe food additive by the FDA¹³. Previous studies have shown that trehalose has the potential to treat various diseases by exerting antitumour, immunomodulatory, and anti-inflammatory effects^14,15. Trehalose has also been recommended for the treatment of lifestyle-related diseases, such as type 2 diabetes^16,17. Furthermore, a recent study suggested that natural disaccharides, including trehalose and fibrulose, reshaped the gut microbiota in vitro¹⁸. Interestingly, while SAP is associated with decreased gut microbial carbohydrate metabolism in mice, we found that this change was reversed and that gut microbial carbohydrate metabolism was significantly increased by depletion of the gut microbiota, especially trehalose. Considering the role of trehalose in reshaping the gut microbiota¹⁹, we hypothesize that trehalose participates in the “microbial metabolism‒gut‒pancreatic axis” in SAP.

Here, we established a mouse model of SAP by administering caerulein and lipopolysaccharide (LPS). The administration of an antibiotic cocktail (ATBx) to treat wild-type (WT) mice, trehalose treatment to WT mice and faecal microbiota transplantation (FMT) to germ-free (GF) mice demonstrated that trehalose ameliorated SAP through the “microbiota‒gut‒pancreatic axis”. Furthermore, we assessed changes in the gut microbiota and microbial metabolism by multi-omics analysis. In this study, we investigated the mechanisms by which SAP-induced alterations in gut microbial metabolism impact both local and systemic inflammatory responses. The study flow was shown in Supplementary Fig. 1a. On the basis of our findings, we provide novel perspectives for the field of SAP treatment, particularly focusing on the role of trehalose in the “microbial metabolism-gut-pancreatic axis”.

Results

Bacterial depletion ameliorates pancreatic injury and the inflammatory response in SAP

To investigate whether the gut microbiota is involved in SAP progression, ATBx treatment was used to deplete the gut microbiota of mice. As shown in Supplementary Fig. 2a–c, ATBx treatment led to a significant reduction in both the diversity and composition of gut microbiota. WT mice were divided into four groups: the blank control (BC), ATBx, SAP, and ATBx-SAP groups (Fig. 1a). Compared with those in the SAP group, pancreatic inflammation and necrosis were significantly decreased in the ATBx-SAP group, as shown by haematoxylin and eosin (H&E) staining (Fig. 1b, c), and serum amylase levels were decreased in the ATBx-SAP group (Supplementary Fig. 2d). These results suggest that depletion of bacteria in the gut ameliorates SAP-related pancreatic injury.

Fig. 1 — a Schematic showing the ATBx treatment approach. b Representative images of H&E-stained pancreas sections. Scale bar = 50 μm. c Histological scores of H&E-stained pancreas sections (BC, n = 12; ATBx, n = 12; SAP, n = 12; ATBx-SAP, n = 12; two biological repeats). d Serum TG levels. e Serum levels of 23 inflammatory cytokines in the groups (SAP vs. BC; ATBx-SAP vs. SAP). ^*p < 0.05, ^**p < 0.01, ^***p < 0.001. BC blank control, SAP severe acute pancreatitis, ATBx antibiotic combination treatment, TG triglyceride, TC total cholesterol, HDL-C high-density lipoprotein cholesterol, LDL-C low-density lipoprotein cholesterol, HE haematoxylin and eosin, NS not significant.

Additionally, the levels of all 23 inflammatory mediators were increased in the SAP group, but the levels of IL-6, IL-17A, IFN-γ, TNF-α, and IL-4 were significantly reduced after ATBx treatment (Fig. 1e). In addition, we previously showed that high triglyceride (TG) levels affect pancreatic injury in pancreatitis²⁰. As shown in Fig. 1d and Supplementary Fig. 2e, the serum TG and total cholesterol (TC) levels were greater in the SAP group, and ATBx treatment significantly reduced the serum TG concentrations. Our data suggest that depletion of the bacteria in the gut is beneficial for reducing inflammation and improving metabolic abnormalities associated with SAP.

Bacterial depletion reverses the SAP-induced imbalance in gut microbial metabolism

To explore the role of gut microbial metabolism in SAP, the composition of the gut microbiota and indices of microbial metabolism were analysed. PCoA revealed distinct microbial compositions in the BC, ATBx, and SAP groups (Fig. 2a). Taking the BC group as a reference, the 10 taxonomic phyla and families with the highest abundances are presented, along with the proportion of changes in each group (Fig. 2b). At the phylum level, the abundances of Firmicutes and Desulfobacterota decreased and the abundances of Proteobacteria and Verrucomicrobia increased in the SAP group compared with BC group (LDA score > 3.5) (Fig. 2c). At the family level, the abundances of Lachnospiraceae, Erysipelotrichaceae, and Desulfovibrionaceae decreased and the abundances of Enterobacteriaceae, Akkermansiaceae, and Lactobacillaceae increased in the SAP group compared with the BC group (Fig. 2c). The abundances of Proteobacteria and Enterobacteriaceae at the phylum and family levels significantly increased after ATBx treatment, accounting for more than 80% of the total bacteria in the ATBx group and more than 60% of the total bacteria in the ATBx-SAP group (Fig. 2b, d and Supplementary Fig. 3a, b). These data suggest that significant gut microbiota disorder is associated with SAP and that the gut microbiota is indeed largely depleted after ATBx treatment.

Fig. 2 — a PCoA plot of the gut microbiota from different groups (BC, n = 11; ATBx, n = 12; SAP, n = 10; ATBx-SAP, n = 12; two biological repeats). b The 10 microbial taxa with the highest abundances at the phylum and family levels (p phylum, f family). c, d Histogram of LDA distribution from LEfSe analysis for significantly different microorganisms in the SAP vs. BC and ATBx-SAP vs. SAP groups, and the microorganisms highlighted in red are among the 10 with the highest abundance. e PCA plot of the gut microbial metabolism of the different groups (BC, n = 11; ATBx, n = 12; SAP, n = 10; ATBx-SAP, n = 12). f, g Volcano plot of microbial metabolites in the SAP vs. BC group and the ATBX-SAP vs. SAP group (p < 0.001, FC ≥ 2 or ≤ 0.5) and donut chart of differentially abundant metabolite class distributions. h Histogram showing the distribution of overall microbial metabolism abundances in the BC group and the proportions of fatty acyls, glycerophospholipids, carboxylic acids and derivatives, and organooxygen compounds in the overall metabolite classes. i Venn diagram of all the differentially abundant metabolites between the SAP and BC groups and between the ATBx-SAP and SAP groups. j Class enrichment of 112 metabolites with altered abundances identified by ChemRICH. The node size represents the total compound number for each cluster set, and the cluster colour represents the proportion of compounds with increased abundance (red = increased, blue = decreased); only the enrichment clusters significantly differing at p < 0.05 are shown. k Lollipop chart showing changes in the levels of carboxylic acids and derivatives, as well as organooxygen compounds involved in the microbial metabolism of the SAP vs. BC group and the ATBx-SAP vs. SAP group. l Schematic diagram showing that ATBx treatment reversed the SAP-induced imbalance in microbial metabolism in the gut. PCoA principal coordinate analysis, PCA principal component analysis, ChemRICH chemical similarity enrichment analysis, LEfSe linear discriminant analysis effect size, LDA linear discriminant analysis. XlogP x-axis of mediation logarithmic additive octanol‒water partition coefficients.

Next, to resolve the gut metabolites associated with gut microbiota disorder in SAP mice, metabolomics analysis was used to evaluate changes in the metabolic components of each group. PCA revealed a clear separation of the metabolic components of the BC, ATBX, and SAP groups (Fig. 2e). For metabolites whose abundances were significantly different in the SAP group vs. the BC group (fold change ≥ 2 or ≤ 0.5 and p ≤ 0.001), we showed the distribution of the top 10 metabolic classes. In the SAP vs. BC group comparison, the microbial metabolites with increased abundances were dominated by those derived from lipid metabolism, with 29.82% and 17.54% fatty acyls and glycerophospholipids, respectively. The microbial metabolites with decreased abundances were dominated by those derived from carbohydrate and amino acid metabolism, with 33.33% and 8.51% of carboxylic acids and derivatives and organooxygen compounds, respectively (Fig. 2f and Supplementary Fig. 3c). Compared with the BC or SAP group, the ATBx treatment group exhibited opposite differences in the abundances of significantly altered gut microbial metabolites (Fig. 2g and Supplementary Fig. 3d, e). These data suggest that gut microbial metabolism is similarly imbalanced along with gut microbiota disorders in SAP.

Indeed, according to the ecological distribution of the overall abundance of microbial metabolites in the BC group, the overall abundances of fatty acyls and glycerophospholipids were essentially equal to those of carboxylic acids and derivatives as well as organooxygen compounds (Fig. 2h). ATBx treatment decreased the overall abundance of microbial metabolites; specifically, it increased fatty acyl and glycerophospholipid levels and decreased carboxylic acid and derivative as well as organooxygen compound levels (Supplementary Fig. 4a–c). To analyse the effects of ATBx treatment on SAP-induced microbial metabolism imbalance more directly, the metabolites at the intersection of the ATBx-SAP vs. SAP group and the SAP vs. BC group were analysed (Fig. 2i). ChemRICH class enrichment revealed that SAP-induced changes in microbial metabolism were opposite those observed after ATBx treatment (Fig. 2j). Specifically, for carboxylic acids and their derivatives as well as organooxygen compounds, the metabolites whose abundances significantly increased after depletion of the gut microbiota mainly included oligosaccharides and peptides, with significant changes in trehalose (Fig. 2k). And trehalose levels in the gut was a correlation with alterations in the gut microbiota (Supplementary Fig. 4d). These findings indicate that bacterial depletion reverses SAP-induced microbial metabolism imbalances (Fig. 2l). On the basis of these data, we hypothesized that trehalose in oligosaccharides is involved in SAP progression.

Trehalose ameliorates the severity of severe acute pancreatitis

Trehalose has been shown to play a beneficial role in the treatment of various diseases²¹. Considering these previous results, we further determined whether trehalose has a beneficial effect on SAP. WT mice were randomized into the BC, trehalose (Tre), SAP, and Tre-SAP groups, and a graded dose of trehalose was orally administered daily for 15 days (Fig. 3a). The Tre group, fed 0.2% trehalose, served as a control to assess any potential side effects of trehalose. Compared with those in the SAP group, pancreatic inflammation and necrosis were significantly alleviated in the Tre-SAP group that was treated with 0.2%, 0.5%, 1%, or 2% trehalose (Fig. 3b, c). 5% trehalose did not affect the pancreatic pathology of SAP, and we found that 40% of the mice exhibited mild enteritis changes in the ileum, accompanied by diarrhea and increased urination in the 5% Tre group (Supplementary Fig. 5a). Serum amylase levels were not altered after trehalose treatment (Supplementary Fig. 5b). These data confirm that trehalose can ameliorate pancreatic injury in SAP.

Moreover, trehalose treatment effectively suppressed the SAP-induced increases in the TG levels but not the TC levels (Fig. 3d and Supplementary Fig. 5c). According to the inflammatory cytokine profile, 0.2% trehalose significantly reduced the expression of TNF-α, MCP-1, IL-6, and IL-17A in the SAP group, and the MCP-1 and TNF-α levels were significantly lower in the Tre group than in the BC group (Fig. 3e–g). These findings suggest that trehalose treatment ameliorates the inflammatory response and metabolic abnormalities associated with SAP.

Trehalose modulates gut microbial metabolism homeostasis in SAP

Considering the significant change in trehalose content that was observed in the ATBx-SAP group, we further explored whether trehalose could affect the gut microbiota and microbial metabolism. Differences in the gut microbiota and microbial metabolism among the BC, 0.2% Tre, SAP, and 0.2% Tre-SAP groups were analysed. PCoA revealed that the gut microbiota in the BC, 0.2% Tre, and SAP groups was entirely separated (Fig. 4a). At the phylum level, there were increases in the abundances of Bacteroidota and Proteobacteria and decreases in the abundances of Firmicutes and Deferribacterota in the Tre group compared with the BC group, and trehalose significantly increased the abundance of Bacteroidota and decreased the abundance Firmicutes in the SAP group (Fig. 4b–d and Supplementary Fig. 6a). At the family level, the abundance of Muribaculaceae increased, whereas that of Lactobacillaceae decreased in the Tre and Tre-SAP groups (Fig. 4b–d and Supplementary Fig. 6b). Taken together, these findings confirm that trehalose treatment can modulate gut microbiota disorders, specifically by increasing the abundance of Muribaculaceae and decreasing the abundance of Lactobacillaceae. Notably, these changes appear to be independent of the dosage of trehalose, as no significant differences were observed in the gut microbiota alterations induced by 0.2% and 2% trehalose (Supplementary Fig. 6c–e).

Additionally, PCA revealed a small difference between the SAP and Tre-SAP groups (Fig. 4e). Compared with those in the BC group, the metabolites whose abundances were increased in the SAP group predominantly include fatty acyls and glycerophospholipids, and the metabolites whose abundances decreased predominantly included carboxylic acids and derivatives as well as organooxygen compounds, which is consistent with previous data (Fig. 4f). According to the previous screening criteria (fold change ≥ 2 or ≤ 0.5 and p ≤ 0.001), few significantly differently abundant metabolites were detected between the Tre-SAP and SAP groups (Fig. 4g and Supplementary Fig. 7a). These findings suggested that trehalose treatment did not cause changes in gut microbial metabolism that were as dramatic and significant as those induced by ATBx treatment. Therefore, we choose another commonly used analytical model, namely, the OPLS-DA model (Supplementary Fig. 7b). Trehalose treatment significantly altered the abundances of 74 metabolites at the intersection of the Tre-SAP vs. SAP group and the Tre vs. BC group (VIP ≥ 1) (Supplementary Fig. 7c). Carboxylic acids and derivatives as well as organooxygen compounds were the main classes enriched with increased metabolites, whereas carboxylic acids and derivatives as well as fatty acyls were the main classes enriched with decreased metabolites (Supplementary Fig. 7d). Moreover, the abundances of 93 metabolites were significantly altered at the intersection of the Tre-SAP vs. SAP group and the SAP vs. BC group (VIP ≥ 1) (Fig. 4h). Trehalose treatment reversed the SAP-associated decrease in the abundances of organooxygen compounds and suppressed the SAP-associated increases in the abundances of fatty acyls (Fig. 4i). ChemRICH class enrichment also revealed that trehalose treatment resulted in a decreased abundance of fatty acyls and an increased abundance of organooxygen compounds in the Tre-SAP group compared with the SAP group (Fig. 4j–k). These results indicate that trehalose ameliorates SAP by modulating gut microbial metabolism, specifically increasing carbohydrate metabolism and decreasing lipid metabolism.

Furthermore, for significantly different metabolites after trehalose treatment, pathway enrichment analysis revealed that the pathways significantly associated with trehalose were galactose metabolism, the pentose phosphate pathway, and the biosynthesis of unsaturated fatty acids (p < 0.01) (Fig. 4m). The metabolites related to trehalose were D-(+)-galactose and inositol, which are involved in galactose metabolism, and these metabolites were increased by trehalose in the Tre-SAP vs. SAP group compared with the SAP vs. BC group (Fig. 4n). In the unsaturated fatty acid biosynthesis pathway, the contents of 16-hydroxyhexadecanoic acid, arachidonic acid and 8Z,11Z,14Z-eicosatrienoic acid were decreased by trehalose (Fig. 4n). Similarly, D-(+)-galactose was increased at the intersection of the Tre-SAP vs. SAP group and the SAP vs. BC group (Supplementary Fig. 7e). Taken together, these findings suggest that galactose metabolism is a key factor in the trehalose-mediated “microbial metabolism-gut-pancreatic axis”.

Trehalose ameliorates SAP in a gut microbiota-dependent manner

To further determine whether the role of trehalose depends on the gut microbiota, we conducted FMT from BC or Tre mice into GF mice and labelled these groups the “BC-FMT” and “Tre-FMT” groups, respectively (Fig. 5a). In the GF mice, trehalose treatment did not ameliorate SAP but instead increased serum keratinocyte-derived chemokine (KC) and IL-10 levels (Fig. 5b–e). After FMT, pancreatic inflammation and necrosis were significantly greater in the BC-FMT-SAP group than in the SAP group, and pathological scores were lower in the Tre-FMT-SAP group than in the BC-FMT-SAP group (Fig. 5b, c). Similar to trehalose treatment, the trehalose-remodelled gut microbiota did not reduce serum amylase levels in the Tre-FMT-SAP group (Fig. 5d). The serum TG level increased after FMT into GF mice, and the trehalose-remodelled microbiota modulated this change (Fig. 5f). Moreover, the serum TNF-α, IL-6 and IL-17A levels were lower in the Tre-FMT-SAP group than in the BC-FMT-SAP group (Fig. 5g). These data confirm that the role of trehalose in SAP depends on the gut microbiota.

Fig. 5 — a Schematic of the FMT experiment in GF mice. b Representative images of H&E-stained pancreas sections from GF mice with SAP after FMT. Scale bar = 50 μm (SAP, n = 12; Tre-SAP, n = 12; BC-FMT-SAP, n = 12; Tre-FMT-SAP, n = 12; two biological repeats). c Histological scores of H&E-stained pancreas sections from GF mice with SAP after FMT (12 mice/group). d Serum amylase levels in each group of GF mice. e, f Serum levels of 23 inflammatory cytokines in GF mice with SAP (Tre-SAP vs. SAP; Tre-FMT-SAP vs. BC-FMT-SAP). g Levels of four lipids (TG, TC, HDL-C, LDL-C) after FMT into GF mice with SAP. ^*p < 0.05, ^**p < 0.01, ^***p < 0.001. FMT faecal microbiota transplantation, NS not significant.

Galactose metabolism and Muribaculaceae are key factors in the trehalose-induced “microbial metabolism-gut-pancreatic axis”

To further understand the effects of trehalose on the “microbial metabolism-gut-pancreatic axis” in SAP, the gut microbiota and microbial metabolism were analysed after FMT into GF mice. There were some differences in the gut microbiota between the BC-FMT-SAP and Tre-FMT-SAP groups (Fig. 6a). Among the 10 phyla (families) with the highest abundances, as in WT mice, Bacteroides (Muribaculaceae), Verrucomicrobiota (Akkermansiaceae) and Firmicutes (Lactobacillaceae) were still overwhelmingly dominant in the gut microbiota of GF mice after FMT (Fig. 6b). LEfSe analysis at the phylum and family levels (LDA score > 3.5) revealed increased abundances of Bacteroidota and Muribaculaceae and decreased abundances of Firmicutes and Lactobacillaceae in the Tre-FMT-SAP group compared with the BC-FMT-SAP group (Fig. 6c). These findings are similar to the results that were obtained after trehalose treatment, further suggesting that Muribaculaceae plays a key role in mediating the effect of trehalose.

There was also a significant difference in gut microbial metabolism between the BC-FMT-SAP and Tre-FMT-SAP groups (Fig. 6d, e). According to ChemRICH class enrichment analysis of 134 differential metabolites (VIP ≥ 1), the abundances of organooxygen compounds, carboxylic acids and derivatives, and glycerophospholipids were increased, while those of fatty acyls were decreased, in Tre-FMT-SAP group compared to the BC-FMT-SAP group (Fig. 6f). For the 19 significantly different metabolites in the Tre-FMT-SAP vs. BC-FMT-SAP groups (VIP ≥ 1 and p < 0.05), the most significantly enriched pathway was galactose metabolism (Fig. 6g, h). These data suggest that galactose metabolism in the gut plays a key role in mediating the effect of trehalose.

To elucidate whether there was a correlation between Muribaculaceae and Lactobacillaceae and significantly different metabolites, a network heatmap was constructed. Muribaculaceae abundance was positively correlated with these metabolites, while Lactobacillaceae abundance was negatively correlated, and D-(+)-galactose (galactose metabolism) and 16-hydroxy hexadecanoic acid (biosynthesis of unsaturated fatty acids) were negatively correlated; these results were consistent with the results observed after the trehalose treatment (Fig. 6i). Thus, we propose that galactose metabolism and Muribaculaceae in the gut microbiota are key factors that mediate the trehalose-mediated “microbial metabolism-gut-pancreatic axis”.

Trehalose reduces macrophage infiltration and caspase-3-mediated apoptosis in the pancreas

The innate immune response, which is dominated by macrophages and neutrophils, is closely related to the severity of acute pancreatitis²². F4/80 and MPO expression were measured in the pancreas. After ATBx treatment, immunohistochemistry (IHC) and immunofluorescence (IF) revealed that pancreatic F4/80 and MPO expression was lower in the ATBx-SAP group than in the SAP group (Fig. 7a). SAP-induced high F4/80 expression was suppressed by trehalose treatment or trehalose-remodelled gut microbiota, whereas MPO expression was not affected by trehalose treatment or trehalose-remodelled gut microbiota (Fig. 7b–d). These data suggest that macrophage infiltration into the pancreas was decreased by trehalose, whereas neutrophil infiltration was not. Therefore, trehalose ameliorates SAP-induced inflammation by regulating macrophages.

Fig. 7 — a–c Representative IHC and IF images of MPO and F4/80 staining in the pancreas after ATBx treatment, trehalose treatment, and FMT (scale bar = 20 µm). d, e IHC and IF quantification of MPO and F4/80 staining in the pancreas after ATBx treatment, trehalose treatment, and FMT (each point represents an individual mouse). ^*p < 0.05, ^**p < 0.01, ^***p < 0.001. NS not significant.

The two programmed cell death pathways, namely, autophagy and apoptosis, are considered to be associated with pancreatitis progression²³. To determine whether the effect of trehalose is related to cell apoptosis and autophagy, we examined the expression levels of Bcl-2, caspase-3, and Beclin1. Bcl-2, caspase-3 and Beclin1 expression were greater in the SAP group than in the BC group (Fig. 8a–c). Notably, the SAP-induced high caspase-3 expression was significantly suppressed by ATBx treatment, trehalose treatment, and trehalose-remodelled gut microbiota, whereas Bcl-2 and Beclin1 expression was not affected (Fig. 8a–c). Quantitative analysis by IHC and IF revealed that the SAP-induced high caspase-3 expression was inhibited in the ATBx-SAP, Tre-SAP, and Tre-FMT-SAP groups (Fig. 8d, e). Although the changes in Bcl-2 expression were not statistically significant (p > 0.05), there was a trend towards increased Bcl-2 expression levels in the ATBx-SAP, Tre-SAP, and Tre-FMT-SAP groups (Fig. 8d, e). Consistent with the IHC and IF results, Western blotting revealed that the SAP-induced high-cleaved caspase-3 expression was suppressed by ATBx treatment, trehalose treatment, and trehalose-remodelled gut microbiota, whereas procaspase-3 expression was increased (Fig. 8f). These results suggest that trehalose ameliorates SAP-induced necrosis by regulating caspase-3-mediated apoptosis.

Fig. 8 — a–c Representative IHC and IF images of Bcl-2, Beclin-1, and caspase-3 expression in the pancreas after ATBx treatment, trehalose treatment, and FMT (scale bar = 20 µm). d, e IHC and IF quantification of Bcl-2, Beclin-1, and caspase-3 expression in the pancreas after ATBx treatment, trehalose treatment, and FMT. f Western blotting images of Bcl-2, Beclin-1, caspase-3, and tubulin protein expression in the pancreas after ATBx treatment, trehalose treatment, and FMT. ^*p < 0.05, ^**p < 0.01, ^***p < 0.001. NS not significant.

Additionally, we found that Beclin1, caspase-3, and MPO were also expressed in pancreatic islets, with Beclin1 expressed in α cells, caspase-3 expressed in α/β cells, and MPO expressed in β cells (Supplementary Fig. 8). Beclin1 and MPO levels in islets did not change during SAP progression; however, caspase-3 expression in islets was increased in the SAP group compared with the BC group, and this increase was suppressed by ATBx treatment. Trehalose treatment or trehalose-remodelled gut microbiota did not affect the SAP-induced increase in caspase-3 expression in islets. These findings suggest that the gut microbiota is involved in islet injury during SAP progression.

Metagenomic and metatranscriptomic alterations of the gut microbiota after ATBx and trehalose treatment

Metagenomic analysis revealed significant changes in the compositions of the gut microbiotas after ATBx treatment. At the phylum level, mice in the ATBx and ATBx+SAP groups showed a marked decrease in Bacteroidota and Firmicutes and an increase in Proteobacteria (Fig. 9a). At the family level, the abundance of Enterobacteriaceae increased substantially in the ATBx-treated groups, whereas Muribaculaceae and Akkermansiaceae were enriched in the control and SAP groups (Fig. 9a). The numbers of non-redundant genes were significantly lower in the ATBx and ATBx+SAP groups than in the SAP and BC groups, indicating antibiotic-induced loss of genetic diversity (Fig. 9b). Moreover, the various groups showed distinct distribution patterns of ARGs, with adeF, vanT, and mdtF being predominant and adeF accounting for over 50% of all induced ARGs (Fig. 9c). Sankey plot analysis revealed that the adeF enrichment in the ATBx+SAP group was mainly linked to Proteobacteria (Alcaligenaceae) and Bacteroidota (Muribaculaceae) (Fig. 9d). adeF was significantly more enriched in the ATBx+SAP group than in the SAP group (Fig. 9e). These results suggest that the increase in Proteobacteria after ATBx treatment may be due to the induction of the adeF gene, which enabled the species to become dominant in the gut microbiota after ATBx treatment.

Fig. 9 — a Taxonomic composition at the phylum (left) and family (right) levels across groups (BC, n = 5; ATBx n = 6; SAP, n = 6; ATBx+SAP, n = 6). b Number of non-redundant genes in different groups. c Relative abundance of major ARGs. d Sankey plots showing associations among ARGs, microbial taxa, and groups. e Comparison of adeF abundance between SAP and ATBx+SAP groups, *p < 0.05. f Density distribution of gene expression across groups. g Heatmaps of COG, CAZy, and KEGG functional categories. h Abundance of key enzyme classes between SAP and ATBx+SAP groups, *p < 0.05. i Volcano plot showing differentially expressed genes (DEGs). j Taxonomic composition of increased and decreased DEGs. k KEGG enrichment analysis of increased (left) and decreased (right) DEGs.

In metatranscriptomic profiling, the density distributions of global gene expression indicated a clear separation between the SAP and ATBx+SAP groups (Fig. 9f). Functional annotation analysis revealed significant differences between the groups, with those associated with auxiliary activities, polysaccharide lyases, and carbohydrate transport/metabolism being significantly increased and those in lipid transport/metabolism significantly decreased after ATBx treatment (Fig. 9g, h). 608 genes that were increased and 64233 that were decreased after ATBx treatment (Fig. 9i). Taxonomic assignment of these genes indicated that the increased transcripts were mainly derived from Proteobacteria (Alcaligenaceae or Enterobacteriaceae), whereas the decreased genes were predominantly associated with Firmicutes (Lachnospiraceae) and Bacteroidota (Muribaculaceae) (Fig. 9j). Moreover, the increased genes were enriched in pathways of tryptophan and nicotinate/nicotinamide metabolism, whereas the decreased genes were largely associated with fatty acid biosynthesis and valine/leucine/isoleucine degradation (Fig. 9k). These results suggest that the metabolic regulation induced by ATBx treatment is attributed to changes in the overall gene expression levels of the microbiota.

For trehalose treatment, metagenomic analysis showed that trehalose treatment increased the abundance of Bacteroidetes (Muribaculaceae) while reducing Firmicutes (Lactobacillaceae) and Verrucomicrobia (Akkermansiaceae) (Supplementary Fig. 9a). The non-redundant gene count revealed no significant difference between the BC and Tre groups, suggesting that trehalose doesn’t alter the overall gut microbiota balance but affects specific strains (Supplementary Fig. 9b). Metatranscriptomic analysis showed minimal overall differences between the BC and Tre groups (Supplementary Fig. 9c). Trehalose treatment increased 15,020 genes and decreased 7162 genes in the gut microbiota (Supplementary Fig. 9d). Increased genes were enriched in pathways like galactose metabolism and ABC transporters, while decreased genes were associated with fatty acid biosynthesis and pyruvate metabolism (Supplementary Fig. 9e), confirming trehalose’s regulatory role in gut microbiota metabolism.

Discussion

Here, we discovered a new function of trehalose, demonstrating its potential to ameliorate SAP through its interaction with the gut microbiota and microbial metabolism (Supplementary Fig. 1b). We found that ATBx treatment, trehalose treatment, and trehalose-remodelled gut microbiota directly increased carbohydrate metabolism and reduced lipid metabolism to ameliorate the imbalance in gut microbial metabolism and inhibited inflammatory cytokine production and cell apoptosis to ultimately ameliorate SAP. Overall, the findings indicate the potential beneficial impact of trehalose treatment on SAP and suggest that trehalose could be a novel gut microbiota-modulating dietary supplement for treating SAP.

Trehalose, an FDA-approved drug, is utilized for treating nervous system diseases and is widely acknowledged as a multitarget therapeutic agent^24,25. Significantly, trehalose has been shown to have positive effects on a mouse model of caerulein-induced AP²⁶. However, the specific molecular mechanisms underlying the effects of trehalose treatment remain undetermined. In this study, we confirmed that trehalose treatment ameliorates pancreatitis and explored the underlying molecular mechanisms. Disturbances in the gut microbiota during SAP pathogenesis and development have received extensive research attention^4,6. Furthermore, potential therapeutic targets in the microbiota‒gut‒pancreatic axis, which modulate the gut microbiota and its metabolites, are considered promising medical treatments for SAP²⁷. We first observed that the gut microbial metabolism imbalance in SAP model mice was reversed after gut microbiota depletion, and significant changes in the abundances of oligosaccharides, including trehalose, were observed. Indeed, trehalose treatment can modulate microbial metabolism imbalances and increase the abundance of the gut probiotic Muribaculaceae. By transplanting the trehalose-remodelled gut microbiota into GF recipients, we confirmed the direct role of the trehalose-remodelled gut microbiota in modulating inflammatory reactions and hyperlipidaemia in SAP. Notably, we observed consistent enrichment of Muribaculaceae, accompanied by increased abundances of organooxygen compounds and decreased abundances of fatty acyls in the WT and GF SAP mouse models. These findings suggest that dietary trehalose supplementation can reverse SAP-induced imbalances in gut microbial metabolism and disorders of the gut microbiota, thereby ameliorating SAP.

Recent research has demonstrated that trehalose treatment can reshape the gut microbiota¹⁸, but the effect of trehalose treatment in SAP-induced gut microbiota disorders remains unclear. The gut microbiota showed an increase in the abundance of Proteobacteria and a decrease in the abundance of Firmicutes in SAP model mice and humans^28,29, which is consistent with our results. We found that trehalose treatment increased the abundance of Bacteroidota and decreased the abundance of Firmicutes in SAP, and Muribaculaceae was the main dominant bacterium in Bacteroidota. We consider that Muribaculaceae may be a key trehalose-related bacterium involved in the microbiota‒gut‒pancreatic axis. Muribaculaceae has previously been revealed to be involved in carbohydrate degradation in the gut and the beneficial effects of dietary polysaccharides^30,31. Moreover, trehalose-remodelled FMT into GF mice revealed that trehalose treatment ameliorates SAP by increasing Muribaculaceae abundance.

Gut microbiota-derived metabolites, such as bile acids, peptidoglycans, and SCFAs, are key regulators of metabolic disorders³². Recent studies have suggested that gut microbiota-derived metabolites are associated with the severity of acute pancreatitis^5,33, but abnormalities in gut microbial metabolism in SAP have not been described in detail. In this study, we first observed a severe imbalance in gut microbial metabolism, which was accompanied by gut microbiota disorders, in SAP model mice, specifically an increase in lipid metabolism and a decrease in carbohydrate and amino acid metabolism. Moreover, trehalose treatment ameliorated inflammation and lipid metabolism in mice and humans with hyperlipidaemia or hyperglycaemia^34–36. Similar to these observations, we found that trehalose treatment not only ameliorated inflammation, necrosis, and hyperlipidaemia in SAP but also partially reversed the SAP-induced imbalance in microbial metabolism. Specifically, trehalose reduced serum MCP-1, IL-1β, IL-6, and TNF-α levels to regulate the inflammatory response^15,37. Our data further confirmed that in the “microbial-gut‒pancreatic axis”, trehalose exerts anti-inflammatory effects by decreasing IL-17A, IL-6, and TNF-α levels. A recent study demonstrated that gut microbial carbohydrate metabolism plays a role in insulin resistance development¹². Similarly, we observed that microbial carbohydrate metabolism was increased and lipid metabolism was decreased after trehalose treatment during SAP progression. The Muribaculaceae abundance in the gut microbiota was positively correlated with the D-(+)-galactose abundance and negatively correlated with the 16-hydroxyhexadecanoic acid abundance. Thus, our findings demonstrate a relationship between dietary supplementation, gut microbial metabolism, and the gut microbiota, highlighting the essential interconnection between gut microbial metabolism and SAP development, i.e., the “microbial metabolism‒gut‒pancreatic axis”.

In this study, we revealed that the trehalose-mediated metabolism‒gut‒pancreatic axis decreased macrophage infiltration and apoptosis, which is considered the main mechanism by which trehalose treatment ameliorates pancreatic inflammation and necrosis in SAP. A recent study reported that glucocorticoids inhibited LPS-induced macrophage-associated inflammatory immune responses through metabolic rewiring³⁸. Similarly, we revealed that trehalose inhibited macrophage infiltration via gut microbial metabolism homeostasis in mice with caerulein- and LPS-induced SAP. Trehalose treatment has been shown to inhibit cell apoptosis across various organs^39–41. It reduced cleaved caspase-3 levels in alveolar macrophages of silicosis, mitigated cadmium-induced hepatic apoptosis via the caspase-dependent pathway, and decreased cleaved caspase-3 in mice with osteoarthritis. Similar to these results, we showed that trehalose increased Bcl-2 expression and decreased caspase-3 activation but had no effect on Beclin-1 expression, suggesting that trehalose treatment ameliorates pancreatic injury by inhibiting caspase-3-mediated apoptosis in SAP. Although trehalose treatment has been reported to modulate pancreatic islet function in individuals with diabetes³⁶, we only found a correlation between the gut microbiota and pancreatic islet injury, and we did not observe an effect of trehalose treatment on islet injury in SAP. However, our study provides new insights into the mechanism underlying trehalose-mediated amelioration of SAP.

Additionally, we conducted metagenomic and metatranscriptomic analyses to explore the molecular mechanisms underlying the structural and metabolic changes in the gut microbiota following ATBx treatment. At the genomic level, we found that ATBx treatment not only reduced the microbial diversity and enriched members of the Proteobacteria but also promoted the expression of specific ARGs, such as adeF. This suggests that antibiotic-resistant populations within Proteobacteria become dominant under selective pressure. These observations are consistent with those of previous studies in which antibiotics significantly reduced the community diversity and enriched ARGs in both human and animal gut microbiotas, indicating an expansion of the resistome under drug selection pressure^42,43. At the transcriptional level, we observed widespread decreased genes in the gut microbiota along with a weakening of their overall metabolic capacity, particularly in pathways related to lipid metabolism. Studies have shown that antibiotics reshape the metabolic transcriptome of microbial communities, inducing systematic effects on the expression of energy metabolism-related genes⁴⁴, which aligns with the metabolic weakening indicated by the metatranscriptomic data. Overall, our results suggest that in the ATBx+SAP group, antibiotics not only alter the community structure but also suppress the metabolic potential of the microbes at the transcriptional level. Additionally, for the metagenome and metatranscriptome of trehalose, we observed results that were largely consistent with 16S rDNA sequencing and metabolomics. These findings provide a possible mechanistic basis for microbiota dysfunction and disease progression.

Several clinical trials worldwide have explored the potential of trehalose in the treatment of a range of conditions, such as Alzheimer’s disease, cardiovascular diseases, dry eye disease, and infertility (https://www.clinicaltrials.gov/), and the injectable trehalose drug SLS-005 has been approved by the FDA for the treatment of spinocerebellar ataxia type 3⁴⁵. Although substantial preclinical evidence has suggested the beneficial effects of trehalose, trehalose has been reported to be associated with the prevalence of Clostridioides difficile infection; however, its use is still controversial^19,46. Surprisingly, we observed that the 5% trehalose did not ameliorate SAP but instead caused diarrhoea and increased urine output in mice, which may be related to the gut disruption induced by a high-sugar diet⁴⁷. Thus, our findings also suggest the role of trehalose in the clinical treatment of SAP.

In general, we provide new insights into the physiological effects of trehalose from three perspectives: the gut, blood, and pancreas; moreover, we show that trehalose treatment modulates the imbalance in gut microbial metabolism to ameliorate SAP. These discoveries not only have potential implications for the use of trehalose in the treatment of SAP but also offer new insights into the “microbial metabolism‒gut‒pancreatic axis”.

Methods

Animal experiments

Six-week-old female C57BL/6 J mice were obtained from GemPharmatech Co., Ltd. (Nanjing, China) and housed under specific pathogen-free (SPF) conditions. All the mice were allowed to acclimate to the laboratory environment for at least 3 days before the experiment was initiated. All animal studies were conducted in accordance with the “Guiding Principles in the Care and Use of Animals” (China). All animal experiment protocol was approved by the Animal Ethics Committee of Jinling Hospital, Nanjing University (Approval No. 2022DZGKJDWLS-0055). At least 2–3 biological replicates were performed for each experiment.

For the antibiotic cocktail treatment (ATBx) group⁴⁸ (n = 5–6/group), a combination of vancomycin (50 mg/mL, Meilunbio, China, Cat. MB1260), imipenem/cilastatin (25 mg/mL, Merck & Co., USA, ATC No. J01DH51), neomycin (10 mg/mL, Sangon Biotech, China, Cat. A610366), and amphotericin (1 mg/mL, Sangon Biotech, China, Cat. A610030) was administered by gavage daily for 5 consecutive days. A combination of vancomycin (0.5 mg/mL), imipenem/cilastatin (0.5 mg/mL), neomycin (1 mg/mL), and amphotericin (0.5 μg/mL) was also added to the drinking water.

For the trehalose (Tre) (MCE, USA, Cat. HY-N1132) diet group (n = 5–6/group), the mice continued to drink water containing 0.2%, 0.5%, 1%, 2%, or 5% trehalose for 15 days. The mice were initially anesthetized through intraperitoneal injection, using a dosage of 80 mg/kg Ketamine and 12 mg/kg Xylazine. Deep anesthesia was confirmed by the absence of a toe pinch reflex and the loss of consciousness. Subsequently, the mice were euthanized via cervical dislocation, following the collection of serum, cecum, and pancreas within a 15-min timeframe. All procedures were performed in strict adherence to ethical guidelines, ensuring humane euthanasia and minimizing distress.

Severe acute pancreatitis model

Caerulein (NJPeptide, China, Cat. Pep03263) was intraperitoneally injected according to body weight (300 µg/kg). One injection was administered per hour for seven total injections. A single intraperitoneal injection of LPS (10 mg/kg, MCE, USA, Cat. HY-D1056) was administered one hour after the last caerulein injection. The control group was injected with an equal amount of phosphate-buffered saline (PBS). The first injection of caerulein was administered at 0 h, and the mice were sacrificed after 24 h; then, the pancreas, serum, caecum, and intestinal faecal contents were harvested.

Histopathological evaluation

Pancreatic tissues were fixed in 4% paraformaldehyde for 24 h. The samples were embedded in paraffin and sectioned (thickness of 4 μm). The sections were stained with haematoxylin and eosin (HE) for pathological histological examination. Ten microscopic fields of view (200× magnification) were randomly selected from each section. Each section was scored by three independent investigators using a previously established scoring system for histopathology as follows: oedema (0–4 scale), number of acinar necrotic cells (0–4 scale), number of intralobular or perivascular leukocytes (0–4 scale), and haemorrhage and fat necrosis (0–4 scale)⁴⁹.

Faecal microbial transplantation (FMT)

Five-week-old female germ-free mice were obtained from GemPharmatech Co., Ltd. (Nanjing, China). Six-week-old female C57BL/6 J mice were administered 0.2% trehalose in their drinking water for 15 days. Then, their intestinal faecal contents were placed in a faecal microbial protection solution (saline containing 30% glycerol and 0.1% cysteine). The faecal microbial protection solution was added at a ratio of 1:3. Each germ-free mouse was subsequently administered 20 µL/g of faecal suspension 3 times a week by gavage. The faecal microorganisms for each gavage included a mixture of the intestinal faecal contents from five C57BL/6 J mice.

16S rRNA gene sequencing analysis

Total microbial DNA was extracted from faecal contents using a Magnetic Soil and Stool DNA Kit (TianGen, China). DNA purity and concentration were then evaluated by electrophoresis on a 1.2% agarose gel. DNA samples were used as templates to amplify the V4 region of the bacterial 16S rRNA gene by PCR. According to the requirements of the Illumina NovaSeq sequencing platform, two-way sequencing was performed, and libraries were constructed using a two-step PCR amplification method with a TruSeq® DNA PCR-Free Sample Preparation Kit (San Diego, USA). The PCR amplification products were recovered with an AXYGEN AxyPrepDNA Gel Recovery Kit (California, USA) and quantified with an FTC-3000^TM real-time PCR instrument.

The sequencing of the PCR amplification products was performed on an Illumina NovaSeq 6000 platform at Novozymes Technology Co. (Beijing, China). The raw data obtained from sequencing were spliced and filtered to obtain clean data. Operational taxonomic unit (OTU) clustering was performed with 97% identity. Species annotation was performed on the OTU sequences, and species annotation analysis was performed using the SSUrRNA database of SILVA138 (http://www.arb-silva.de/) using the Mothur method (threshold value of 0.8-1). Rapid multiple sequence alignment was performed using MUSCLE (version 3.8.31, http://www.drive5.com/muscle/) software to determine the phylogenetic relationships of all representative OTU sequences. Beta diversity index intergroup variance analysis using R software and LEfSe analysis using linear discriminant analysis (LDA) effect size (LEfSe) software were performed (LDA score (log10) = 3.5 as the cut-off value).

Metabolomic analysis

Metabolomics based on ultrahigh-performance liquid chromatography (UHPLC) coupled with high-resolution mass spectrometry (MS) was performed by Novozymes Technology Co. (Beijing, China). One hundred-milligram samples containing faecal contents were individually homogenized in liquid nitrogen, and the homogenates were resuspended in prechilled 80% methanol by vortexing. Some of the supernatants were diluted to a final concentration of 53% methanol with liquid chromatography–mass spectrometry (LC‒MS)-grade water. Finally, the supernatants were injected into the LC‒MS‒MS/MS system for analysis.

The raw UHPLC‒MS/MS data were imported into Compound Discoverer 3.1 software, and the spectra were processed and compared with the mzCloud, mzVault, and Masslist databases. The raw quantitative results were normalized to obtain the identification and relative quantitative data of the metabolites. MetaX was utilized to preprocess the data and conduct principal component analysis (PCA) as well as orthogonal partial least squares discriminant analysis (OPLS-DA) to derive the variable importance in projection (VIP) scores for each metabolite. The p value was calculated to assess the difference in the levels of each metabolite between the two groups via univariate analysis (t-test). The default criteria for differentially abundant metabolite screening were VIP ≥ 1 and p value < 0.05 or fold change (FC) ≥ 2 or FC ≤ 0.5 and p value < 0.001. Chemical similarity enrichment analysis was performed using ChemRICH (http://chemrich.fiehnlab.ucdavis.edu/)⁵⁰. Pathway enrichment analysis was conducted using MetaboAnalyst 6.0⁵¹.

Metagenomic and metatranscriptomic analyses

Mouse fecal DNA and RNA were extracted and sequenced on the Illumina NovaSeq 6000 platform⁵². Raw reads were quality filtered using fastp (v0.20.0), and host-derived sequences were removed using Bowtie2 (v2.3.5.1) and Hisat2 (v2.1.0). Sequence assembly was performed with MEGAHIT (v1.2.9) for the metagenomes and Trinity (v2.11.0) for the metatranscriptomes, and ORFs were predicted with Prodigal (v2.6.3) or TransDecoder (v5.5.0) and clustered into non-redundant gene sets using CD-HIT (v4.8.1). Gene abundance and expression levels were estimated using BWA (v0.7.17) and RSEM, respectively, and differential expression was analyzed with DESeq2. Functional annotation against the KEGG, COG, GO, SwissProt, Pfam, CAZy, VFDB, and CARD databases was conducted using DIAMOND (v2.0.6.144), RGI, blastall, and HMMER. Taxonomic classification was performed with Kraken2 (v2.1.2), and the abundance profiles were subjected to community structure, multivariate, clustering, and differential taxa analyses to characterize the compositions of the microorganisms and their active functions.

Cytokine analysis

A Bio-Plex Pro Mouse Cytokine 23-plex Assay Kit (California, USA) was used to measure the levels of 23 inflammatory cytokines, including IL-1α, IL-1β, IL-2, IL-3, IL-4, IL-5, IL-6, IL-9, IL-10, IL-12 (p40), IL-12 (p70), IL-13, IL-17A, eotaxin, G-CSF, GM-CSF, IFN-γ, KC, MCP-1 (MCAF), MIP-1α, MIP-1β, RANTES and TNF-α. Assays based on liquid chip technology were performed on a Luminex 200 System by Shanghai Universal Biotech Co. (Shanghai, China).

Lipid analysis

The biochemical assessment of lipids followed the World Health Organization lipid reference standards. The levels of low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), triglyceride (TG), and total cholesterol (TC) concentrations were measured enzymatically using a Hitachi 7600 automated analyser (Kyowa, Japan). Mouse serum was analysed within 30 min of sample collection.

Immunohistochemical analysis

After the paraffin blocks were dewaxed and rehydrated, the pancreatic tissues were blocked with 5% bovine serum albumin for 30 min and washed with PBS. The tissue sections were incubated with antibodies against Bcl-2 (1:1000, Servicebio, Cat. GB114830), Beclin-1 (1:1000, Servicebio, Cat. GB11228), caspase-3 (1:100, Servicebio, Cat. GB11009-1), MPO (1:500, Servicebio, Cat. GB11224) and F4/80 (1:500, Servicebio, Cat. GB113373) for 12 h. After the membranes were washed 3 times with PBS, they were incubated with a peroxidase-conjugated secondary antibody for 2 h. Staining was monitored under a microscope and terminated when adequate. The slides were then dehydrated and stored. Images of the tissues were captured using a microscope (400× magnification). The intensity of specific staining was measured using Image-Pro Plus 6.0 (Media Cybernetics, Silver Spring, MD, USA). Ten fields of view were randomly selected for each section. For Bcl-2, caspase-3, and Beclin-1, the ratio of the positively stained area to the total area was determined. For MPO and F4/80, the number of positively stained cells was determined. All the images were acquired using the same microscope and camera.

Immunofluorescence staining

The tissue was embedded in paraffin and then sectioned at a thickness of 4 µm. Antigen retrieval was performed using EDTA antigen retrieval solution, followed by blocking nonspecific binding with 3% BSA for 30 min. Subsequently, the tissues were incubated with antibodies against Bcl-2 (1:800, Servicebio, Cat. GB114830), Beclin-1 (1:1000, Servicebio, Cat. GB11228), caspase-3 (1:200, Servicebio, Cat. GB11009-1), MPO (1:500, Servicebio, Cat. GB11224) and F4/80 (1:500, Servicebio, Cat. GB113373) overnight at 4 °C. After a 1-h incubation with CY3-conjugated secondary antibodies (Servicebio), the tissues were counterstained with DAPI to visualize the nuclei. Images were subsequently acquired using a fluorescence microscope (Nikon Eclipse C1, Nikon, Japan). Image-Pro Plus 6.0 was used to analyse the fluorescence intensity.

Western blotting analysis

Total protein was extracted from pancreatic tissues with a low-temperature tissue grinder. In accordance with our previously described methods⁵³, an equal quantity of protein from each sample was subjected to 10% SDS‒PAGE and subsequent Western blotting assays using anti-Bcl-2 (1:1000, Abways, Cat. CY6717), anti-Beclin-1 (1:1000, ABclonal, Cat. A11761), anti-caspase-3 (1:1000, Proteintech, Cat. 66470–2-Ig) and anti-Tubulin (1:10,000, Proteintech, Cat. 66031-1-IG) antibodies. After incubation with the corresponding secondary antibody, the bands were detected using enhanced chemiluminescence (ECL) reagents. Three biological repeats were included in the WB analyses.

Statistical analysis

The data are presented as the means ± SEMs. Differences between two groups were assessed using a two-tailed unpaired Student’s t-test. Differences among more than two groups were assessed using analysis of variance (ANOVA), and multiple comparisons were performed for all pairs using the Tukey‒Kramer test. For the analysis of the microbiota sequencing data, a two-tailed Wilcoxon rank-sum test was performed between the two groups. p < 0.05 was considered to indicate a significant difference. Statistical analysis and graphing were performed using R software (v 4.2.2) and GraphPad Prism (v 8.0.2).

Supplementary information

Supplementary information^{(1.7MB, pdf)}

Acknowledgements

We would like to thank Prof. Yangchao Chen for technical assistance. This work was funded by the National Natural Science Foundation of China (82270678, 82102275, and 82070669), and Postdoctoral Fellowship Project (97157).

Author contributions

W.Q.L. and Z.H.T.: Conceptualization, funding acquisition, and methodology. S.W.S.: Conceptualization, visualization, and methodology. H.B.H. and D.R.D.: Conceptualization, project administration, writing—original draft, and writing— review and editing. H.L.: Data curation, methodology, and Writing—review and editing. W.L. and Y.Z.L.: Data curation and methodology. G.H.H.: Data curation and Writing—review and editing. Y.X.L. and C.L.S.: Software, data curation, and investigation. L.L.L.: Resources and Supervision. L.K.: Conceptualization, supervision, and writing–review and editing. A.K.F.: Conceptualization and writing—review and editing.

Data availability

All the gene sequence data were obtained from the National Genomics Data Center (NGDC), which is part of the China National Center for Bioinformation (CNCB) database under accession code PRJCA026291.

Competing interests

The authors declare no competing interests.

Footnotes

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

These authors contributed equally: Haibin Hao, Deren Du, Hong Lin.

Contributor Information

Shengwen Shao, Email: shaoshw@zjhu.edu.cn.

Weiqin Li, Email: liweiqindr@nju.edu.cn.

Zhihui Tong, Email: tongzhihui@nju.edu.cn.

Supplementary information

The online version contains supplementary material available at 10.1038/s41522-026-00950-8.

References

1.Boxhoorn, L. et al. Acute pancreatitis. Lancet396, 726–734 (2020). [DOI] [PubMed] [Google Scholar]
2.Schepers, N. J. et al. Impact of characteristics of organ failure and infected necrosis on mortality in necrotising pancreatitis. Gut68, 1044–1051 (2019). [DOI] [PubMed] [Google Scholar]
3.Gliem, N., Ammer-Herrmenau, C., Ellenrieder, V. & Neesse, A. Management of severe acute pancreatitis: an update. Digestion102, 503–507 (2021). [DOI] [PMC free article] [PubMed] [Google Scholar]
4.Zhu, Y. et al. Gut microbiota dysbiosis worsens the severity of acute pancreatitis in patients and mice. J. Gastroenterol.54, 347–358 (2019). [DOI] [PubMed] [Google Scholar]
5.Ammer-Herrmenau, C. et al. Gut microbiota predicts severity and reveals novel metabolic signatures in acute pancreatitis. Gut73, 485–495 (2024). [DOI] [PMC free article] [PubMed] [Google Scholar]
6.Yu, S. et al. Identification of dysfunctional gut microbiota through rectal swab in patients with different severity of acute pancreatitis. Dig. Dis. Sci.65, 3223–3237 (2020). [DOI] [PubMed] [Google Scholar]
7.Li, H. et al. Bifidobacterium spp. and their metabolite lactate protect against acute pancreatitis via inhibition of pancreatic and systemic inflammatory responses. Gut Microbes14, 2127456 (2022). [DOI] [PMC free article] [PubMed] [Google Scholar]
8.Mei, Q. X. et al. Pretreatment with chitosan oligosaccharides attenuate experimental severe acute pancreatitis via inhibiting oxidative stress and modulating intestinal homeostasis. Acta Pharmacol. Sin.42, 942–953 (2021). [DOI] [PMC free article] [PubMed] [Google Scholar]
9.Zhao, H. B., Jia, L., Yan, Q. Q., Deng, Q. & Wei, B. Effect of clostridium butyricum and butyrate on intestinal barrier functions: study of a rat model of severe acute pancreatitis with intra-abdominal hypertension. Front. Physiol.11, 561061 (2020). [DOI] [PMC free article] [PubMed] [Google Scholar]
10.Ke, L. et al. Immune enhancement in patients with predicted severe acute necrotising pancreatitis: a multicentre double-blind randomised controlled trial. Intensive Care Med.48, 899–909 (2022). [DOI] [PMC free article] [PubMed] [Google Scholar]
11.Sun, J. K. et al. Early enteral nutrition prevents intra-abdominal hypertension and reduces the severity of severe acute pancreatitis compared with delayed enteral nutrition: a prospective pilot study. World J. Surg.37, 2053–2060 (2013). [DOI] [PubMed] [Google Scholar]
12.Takeuchi, T. et al. Gut microbial carbohydrate metabolism contributes to insulin resistance. Nature621, 389–395 (2023). [DOI] [PMC free article] [PubMed] [Google Scholar]
13.Ohtake, S. & Wang, Y. J. Trehalose: current use and future applications. J. Pharm. Sci.100, 2020–2053 (2011). [DOI] [PubMed] [Google Scholar]
14.Del, B. B., Gamberucci, A., Marcolongo, P. & Maellaro, E. The autophagy inducer trehalose stimulates macropinocytosis in NF1-deficient glioblastoma cells. Cancer Cell Int.22, 232 (2022). [DOI] [PMC free article] [PubMed] [Google Scholar]
15.Yu, S., Park, H. & Kim, W. Trehalose inhibits inflammatory responses through mitochondrial reprogramming in RAW 264.7 macrophages. Antioxidants. 12, 1166 (2023). [DOI] [PMC free article] [PubMed]
16.Hashemian, S. et al. The effects of oral trehalose on glycaemia, inflammation, and quality of life in patients with type 2 diabetes: a pilot randomized controlled trial. Arch. Med. Sci.19, 1693–1700 (2023). [DOI] [PMC free article] [PubMed] [Google Scholar]
17.Mizote, A. et al. Daily intake of trehalose is effective in the prevention of lifestyle-related diseases in individuals with risk factors for metabolic syndrome. J. Nutr. Sci. Vitaminol.62, 380–387 (2016). [DOI] [PubMed] [Google Scholar]
18.Onyango, S. O. et al. Glycosidic linkage of rare and new-to-nature disaccharides reshapes gut microbiota in vitro. Food Chem.411, 135440 (2023). [DOI] [PubMed] [Google Scholar]
19.Buckley, A. M. et al. Trehalose-induced remodelling of the human microbiota affects clostridioides difficile infection outcome in an in vitro colonic model: a pilot study. Front. Cell. Infect. Microbiol.11, 670935 (2021). [DOI] [PMC free article] [PubMed] [Google Scholar]
20.Yang, N. et al. Hypertriglyceridaemia delays pancreatic regeneration after acute pancreatitis in mice and patients. Gut68, 378–380 (2019). [DOI] [PMC free article] [PubMed] [Google Scholar]
21.Hosseinpour-Moghaddam, K., Caraglia, M. & Sahebkar, A. Autophagy induction by trehalose: molecular mechanisms and therapeutic impacts. J. Cell. Physiol.233, 6524–6543 (2018). [DOI] [PubMed] [Google Scholar]
22.Hu, F. et al. Macrophages in pancreatitis: mechanisms and therapeutic potential. Biomed. Pharmacother.131, 110693 (2020). [DOI] [PubMed] [Google Scholar]
23.Li, H., Wu, D., Zhang, H. & Li, P. New insights into regulatory cell death and acute pancreatitis. Heliyon9, e18036 (2023). [DOI] [PMC free article] [PubMed] [Google Scholar]
24.Pupyshev, A. B., Klyushnik, T. P., Akopyan, A. A., Singh, S. K. & Tikhonova, M. A. Disaccharide trehalose in experimental therapies for neurodegenerative disorders: molecular targets and translational potential. Pharmacol. Res.183, 106373 (2022). [DOI] [PubMed] [Google Scholar]
25.Kul, E. & Stork, O. Trehalose consumption ameliorates pathogenesis in an inducible mouse model of the Fragile X-associated tremor/ataxia syndrome. Nutr. Neurosci. 27, 826–835 (2023). [DOI] [PubMed]
26.Khamaysi, I. et al. S75 combination of trehalose and heparanase inhibitors treatment ameliorates cerulein-induced acute pancreatitis in a murine model. Am. J. Gastroenterol.116, S32 (2021). [Google Scholar]
27.Gesualdo, M. et al. Pancreatic diseases and microbiota: a literature review and future perspectives. J. Clin. Med. 9, 3535 (2020). [DOI] [PMC free article] [PubMed]
28.Zhang, X. M. et al. Intestinal microbial community differs between acute pancreatitis patients and healthy volunteers. Biomed. Environ. Sci.31, 81–86 (2018). [DOI] [PubMed] [Google Scholar]
29.Jin, M. et al. Colonic interleukin-22 protects intestinal mucosal barrier and microbiota abundance in severe acute pancreatitis. Faseb. J.36, e22174 (2022). [DOI] [PubMed] [Google Scholar]
30.Zhao, T. et al. Impact of structurally diverse polysaccharides on colonic mucin O-glycosylation and gut microbiota. npj Biofilms Microbomes9, 97 (2023). [DOI] [PMC free article] [PubMed] [Google Scholar]
31.Lagkouvardos, I. et al. Sequence and cultivation study of Muribaculaceae reveals novel species, host preference, and functional potential of this yet undescribed family. Microbiome7, 28 (2019). [DOI] [PMC free article] [PubMed] [Google Scholar]
32.Agus, A., Clement, K. & Sokol, H. Gut microbiota-derived metabolites as central regulators in metabolic disorders. Gut70, 1174–1182 (2021). [DOI] [PMC free article] [PubMed] [Google Scholar]
33.Liu, J. et al. Integrative metagenomic and metabolomic analyses reveal the potential of gut microbiota to exacerbate acute pancreatitis. npj Biofilms Microbomes10, 29 (2024). [DOI] [PMC free article] [PubMed] [Google Scholar]
34.Arai, C. et al. Trehalose prevents adipocyte hypertrophy and mitigates insulin resistance. Nutr. Res.30, 840–848 (2010). [DOI] [PubMed] [Google Scholar]
35.Yoshizane, C. et al. Daily consumption of one teaspoon of trehalose can help maintain glucose homeostasis: a double-blind, randomized controlled trial conducted in healthy volunteers. Nutr. J.19, 68 (2020). [DOI] [PMC free article] [PubMed] [Google Scholar]
36.Yaribeygi, H., Yaribeygi, A., Sathyapalan, T. & Sahebkar, A. Molecular mechanisms of trehalose in modulating glucose homeostasis in diabetes. Diabetes Metab. Syndr. Clin. Res. Rev.13, 2214–2218 (2019). [DOI] [PubMed] [Google Scholar]
37.Liu, S. et al. Trehalose attenuates renal ischemia-reperfusion injury by enhancing autophagy and inhibiting oxidative stress and inflammation. Am. J. Physiol. Renal Physiol.318, F994–F1005 (2020). [DOI] [PubMed] [Google Scholar]
38.Auger, J. P. et al. Metabolic rewiring promotes anti-inflammatory effects of glucocorticoids. Nature629, 184–192 (2024). [DOI] [PubMed] [Google Scholar]
39.Tan, S. et al. Trehalose alleviates apoptosis by protecting the autophagy-lysosomal system in alveolar macrophages during human silicosis. Life Sci.257, 118043 (2020). [DOI] [PubMed] [Google Scholar]
40.Gong, Z. G., Wang, X. Y., Wang, J. H., Fan, R. F. & Wang, L. Trehalose prevents cadmium-induced hepatotoxicity by blocking Nrf2 pathway, restoring autophagy and inhibiting apoptosis. J. Inorg. Biochem.192, 62–71 (2019). [DOI] [PubMed] [Google Scholar]
41.Tang, K. K., Liu, X. Y., Wang, Z. Y., Qu, K. C. & Fan, R. F. Trehalose alleviates cadmium-induced brain damage by ameliorating oxidative stress, autophagy inhibition, and apoptosis. Metallomics11, 2043–2051 (2019). [DOI] [PubMed] [Google Scholar]
42.Lee, K. et al. Population-level impacts of antibiotic usage on the human gut microbiome. Nat. Commun.14, 1191 (2023). [DOI] [PMC free article] [PubMed] [Google Scholar]
43.Xu, L. et al. The effect of antibiotics on the gut microbiome: a metagenomics analysis of microbial shift and gut antibiotic resistance in antibiotic treated mice. Bmc Genomics21, 263 (2020). [DOI] [PMC free article] [PubMed] [Google Scholar]
44.Cabral, D. J. et al. Microbial metabolism modulates antibiotic susceptibility within the murine gut microbiome. Cell Metab.30, 800–823 (2019). [DOI] [PMC free article] [PubMed] [Google Scholar]
45.Stahl, F., Evert, B. O., Han, X., Breuer, P. & Wullner, U. Spinocerebellar ataxia type 3 pathophysiology-implications for translational research and clinical studies. Int. J. Mol. Sci. 25, 3984 (2024). [DOI] [PMC free article] [PubMed]
46.Collins, J. et al. Dietary trehalose enhances virulence of epidemic Clostridium difficile. Nature553, 291–294 (2018). [DOI] [PMC free article] [PubMed] [Google Scholar]
47.Kawano, Y. et al. Microbiota imbalance induced by dietary sugar disrupts immune-mediated protection from metabolic syndrome. Cell185, 3501–3519 (2022). [DOI] [PMC free article] [PubMed] [Google Scholar]
48.Fu, A. et al. Tumor-resident intracellular microbiota promotes metastatic colonization in breast cancer. Cell185, 1356–1372 (2022). [DOI] [PubMed] [Google Scholar]
49.Du, D. et al. Differences in glucose homeostasis and islet injury among diverse mice strains post acute pancreatitis. Biochem. Biophys. Res. Commun.708, 149780 (2024). [DOI] [PubMed] [Google Scholar]
50.Barupal, D. K. & Fiehn, O. Chemical similarity enrichment analysis (ChemRICH) as alternative to biochemical pathway mapping for metabolomic datasets. Sci. Rep.7, 14567 (2017). [DOI] [PMC free article] [PubMed] [Google Scholar]
51.Pang, Z. et al. MetaboAnalyst 6.0: towards a unified platform for metabolomics data processing, analysis and interpretation. Nucleic. Acids. Res. 52, W398–W406 (2024). [DOI] [PMC free article] [PubMed]
52.Li, C. et al. Multiomic analysis of different horse breeds reveals that gut microbial butyrate enhances racehorse athletic performance. npj Biofilms Microbomes11, 87 (2025). [DOI] [PMC free article] [PubMed] [Google Scholar]
53.Lu, Y. et al. HDL inhibits pancreatic acinar cell NLRP3 inflammasome activation and protect against acinar cell pyroptosis in acute pancreatitis. Int. Immunopharmacol.125, 110950 (2023). [DOI] [PubMed] [Google Scholar]

Associated Data

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

Supplementary Materials

Supplementary information^{(1.7MB, pdf)}

Data Availability Statement

All the gene sequence data were obtained from the National Genomics Data Center (NGDC), which is part of the China National Center for Bioinformation (CNCB) database under accession code PRJCA026291.

[CR1] 1.Boxhoorn, L. et al. Acute pancreatitis. Lancet396, 726–734 (2020). [DOI] [PubMed] [Google Scholar]

[CR2] 2.Schepers, N. J. et al. Impact of characteristics of organ failure and infected necrosis on mortality in necrotising pancreatitis. Gut68, 1044–1051 (2019). [DOI] [PubMed] [Google Scholar]

[CR3] 3.Gliem, N., Ammer-Herrmenau, C., Ellenrieder, V. & Neesse, A. Management of severe acute pancreatitis: an update. Digestion102, 503–507 (2021). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR4] 4.Zhu, Y. et al. Gut microbiota dysbiosis worsens the severity of acute pancreatitis in patients and mice. J. Gastroenterol.54, 347–358 (2019). [DOI] [PubMed] [Google Scholar]

[CR5] 5.Ammer-Herrmenau, C. et al. Gut microbiota predicts severity and reveals novel metabolic signatures in acute pancreatitis. Gut73, 485–495 (2024). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR6] 6.Yu, S. et al. Identification of dysfunctional gut microbiota through rectal swab in patients with different severity of acute pancreatitis. Dig. Dis. Sci.65, 3223–3237 (2020). [DOI] [PubMed] [Google Scholar]

[CR7] 7.Li, H. et al. Bifidobacterium spp. and their metabolite lactate protect against acute pancreatitis via inhibition of pancreatic and systemic inflammatory responses. Gut Microbes14, 2127456 (2022). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR8] 8.Mei, Q. X. et al. Pretreatment with chitosan oligosaccharides attenuate experimental severe acute pancreatitis via inhibiting oxidative stress and modulating intestinal homeostasis. Acta Pharmacol. Sin.42, 942–953 (2021). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR9] 9.Zhao, H. B., Jia, L., Yan, Q. Q., Deng, Q. & Wei, B. Effect of clostridium butyricum and butyrate on intestinal barrier functions: study of a rat model of severe acute pancreatitis with intra-abdominal hypertension. Front. Physiol.11, 561061 (2020). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR10] 10.Ke, L. et al. Immune enhancement in patients with predicted severe acute necrotising pancreatitis: a multicentre double-blind randomised controlled trial. Intensive Care Med.48, 899–909 (2022). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR11] 11.Sun, J. K. et al. Early enteral nutrition prevents intra-abdominal hypertension and reduces the severity of severe acute pancreatitis compared with delayed enteral nutrition: a prospective pilot study. World J. Surg.37, 2053–2060 (2013). [DOI] [PubMed] [Google Scholar]

[CR12] 12.Takeuchi, T. et al. Gut microbial carbohydrate metabolism contributes to insulin resistance. Nature621, 389–395 (2023). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR13] 13.Ohtake, S. & Wang, Y. J. Trehalose: current use and future applications. J. Pharm. Sci.100, 2020–2053 (2011). [DOI] [PubMed] [Google Scholar]

[CR14] 14.Del, B. B., Gamberucci, A., Marcolongo, P. & Maellaro, E. The autophagy inducer trehalose stimulates macropinocytosis in NF1-deficient glioblastoma cells. Cancer Cell Int.22, 232 (2022). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR15] 15.Yu, S., Park, H. & Kim, W. Trehalose inhibits inflammatory responses through mitochondrial reprogramming in RAW 264.7 macrophages. Antioxidants. 12, 1166 (2023). [DOI] [PMC free article] [PubMed]

[CR16] 16.Hashemian, S. et al. The effects of oral trehalose on glycaemia, inflammation, and quality of life in patients with type 2 diabetes: a pilot randomized controlled trial. Arch. Med. Sci.19, 1693–1700 (2023). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR17] 17.Mizote, A. et al. Daily intake of trehalose is effective in the prevention of lifestyle-related diseases in individuals with risk factors for metabolic syndrome. J. Nutr. Sci. Vitaminol.62, 380–387 (2016). [DOI] [PubMed] [Google Scholar]

[CR18] 18.Onyango, S. O. et al. Glycosidic linkage of rare and new-to-nature disaccharides reshapes gut microbiota in vitro. Food Chem.411, 135440 (2023). [DOI] [PubMed] [Google Scholar]

[CR19] 19.Buckley, A. M. et al. Trehalose-induced remodelling of the human microbiota affects clostridioides difficile infection outcome in an in vitro colonic model: a pilot study. Front. Cell. Infect. Microbiol.11, 670935 (2021). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR20] 20.Yang, N. et al. Hypertriglyceridaemia delays pancreatic regeneration after acute pancreatitis in mice and patients. Gut68, 378–380 (2019). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR21] 21.Hosseinpour-Moghaddam, K., Caraglia, M. & Sahebkar, A. Autophagy induction by trehalose: molecular mechanisms and therapeutic impacts. J. Cell. Physiol.233, 6524–6543 (2018). [DOI] [PubMed] [Google Scholar]

[CR22] 22.Hu, F. et al. Macrophages in pancreatitis: mechanisms and therapeutic potential. Biomed. Pharmacother.131, 110693 (2020). [DOI] [PubMed] [Google Scholar]

[CR23] 23.Li, H., Wu, D., Zhang, H. & Li, P. New insights into regulatory cell death and acute pancreatitis. Heliyon9, e18036 (2023). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR24] 24.Pupyshev, A. B., Klyushnik, T. P., Akopyan, A. A., Singh, S. K. & Tikhonova, M. A. Disaccharide trehalose in experimental therapies for neurodegenerative disorders: molecular targets and translational potential. Pharmacol. Res.183, 106373 (2022). [DOI] [PubMed] [Google Scholar]

[CR25] 25.Kul, E. & Stork, O. Trehalose consumption ameliorates pathogenesis in an inducible mouse model of the Fragile X-associated tremor/ataxia syndrome. Nutr. Neurosci. 27, 826–835 (2023). [DOI] [PubMed]

[CR26] 26.Khamaysi, I. et al. S75 combination of trehalose and heparanase inhibitors treatment ameliorates cerulein-induced acute pancreatitis in a murine model. Am. J. Gastroenterol.116, S32 (2021). [Google Scholar]

[CR27] 27.Gesualdo, M. et al. Pancreatic diseases and microbiota: a literature review and future perspectives. J. Clin. Med. 9, 3535 (2020). [DOI] [PMC free article] [PubMed]

[CR28] 28.Zhang, X. M. et al. Intestinal microbial community differs between acute pancreatitis patients and healthy volunteers. Biomed. Environ. Sci.31, 81–86 (2018). [DOI] [PubMed] [Google Scholar]

[CR29] 29.Jin, M. et al. Colonic interleukin-22 protects intestinal mucosal barrier and microbiota abundance in severe acute pancreatitis. Faseb. J.36, e22174 (2022). [DOI] [PubMed] [Google Scholar]

[CR30] 30.Zhao, T. et al. Impact of structurally diverse polysaccharides on colonic mucin O-glycosylation and gut microbiota. npj Biofilms Microbomes9, 97 (2023). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR31] 31.Lagkouvardos, I. et al. Sequence and cultivation study of Muribaculaceae reveals novel species, host preference, and functional potential of this yet undescribed family. Microbiome7, 28 (2019). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR32] 32.Agus, A., Clement, K. & Sokol, H. Gut microbiota-derived metabolites as central regulators in metabolic disorders. Gut70, 1174–1182 (2021). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR33] 33.Liu, J. et al. Integrative metagenomic and metabolomic analyses reveal the potential of gut microbiota to exacerbate acute pancreatitis. npj Biofilms Microbomes10, 29 (2024). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR34] 34.Arai, C. et al. Trehalose prevents adipocyte hypertrophy and mitigates insulin resistance. Nutr. Res.30, 840–848 (2010). [DOI] [PubMed] [Google Scholar]

[CR35] 35.Yoshizane, C. et al. Daily consumption of one teaspoon of trehalose can help maintain glucose homeostasis: a double-blind, randomized controlled trial conducted in healthy volunteers. Nutr. J.19, 68 (2020). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR36] 36.Yaribeygi, H., Yaribeygi, A., Sathyapalan, T. & Sahebkar, A. Molecular mechanisms of trehalose in modulating glucose homeostasis in diabetes. Diabetes Metab. Syndr. Clin. Res. Rev.13, 2214–2218 (2019). [DOI] [PubMed] [Google Scholar]

[CR37] 37.Liu, S. et al. Trehalose attenuates renal ischemia-reperfusion injury by enhancing autophagy and inhibiting oxidative stress and inflammation. Am. J. Physiol. Renal Physiol.318, F994–F1005 (2020). [DOI] [PubMed] [Google Scholar]

[CR38] 38.Auger, J. P. et al. Metabolic rewiring promotes anti-inflammatory effects of glucocorticoids. Nature629, 184–192 (2024). [DOI] [PubMed] [Google Scholar]

[CR39] 39.Tan, S. et al. Trehalose alleviates apoptosis by protecting the autophagy-lysosomal system in alveolar macrophages during human silicosis. Life Sci.257, 118043 (2020). [DOI] [PubMed] [Google Scholar]

[CR40] 40.Gong, Z. G., Wang, X. Y., Wang, J. H., Fan, R. F. & Wang, L. Trehalose prevents cadmium-induced hepatotoxicity by blocking Nrf2 pathway, restoring autophagy and inhibiting apoptosis. J. Inorg. Biochem.192, 62–71 (2019). [DOI] [PubMed] [Google Scholar]

[CR41] 41.Tang, K. K., Liu, X. Y., Wang, Z. Y., Qu, K. C. & Fan, R. F. Trehalose alleviates cadmium-induced brain damage by ameliorating oxidative stress, autophagy inhibition, and apoptosis. Metallomics11, 2043–2051 (2019). [DOI] [PubMed] [Google Scholar]

[CR42] 42.Lee, K. et al. Population-level impacts of antibiotic usage on the human gut microbiome. Nat. Commun.14, 1191 (2023). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR43] 43.Xu, L. et al. The effect of antibiotics on the gut microbiome: a metagenomics analysis of microbial shift and gut antibiotic resistance in antibiotic treated mice. Bmc Genomics21, 263 (2020). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR44] 44.Cabral, D. J. et al. Microbial metabolism modulates antibiotic susceptibility within the murine gut microbiome. Cell Metab.30, 800–823 (2019). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR45] 45.Stahl, F., Evert, B. O., Han, X., Breuer, P. & Wullner, U. Spinocerebellar ataxia type 3 pathophysiology-implications for translational research and clinical studies. Int. J. Mol. Sci. 25, 3984 (2024). [DOI] [PMC free article] [PubMed]

[CR46] 46.Collins, J. et al. Dietary trehalose enhances virulence of epidemic Clostridium difficile. Nature553, 291–294 (2018). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR47] 47.Kawano, Y. et al. Microbiota imbalance induced by dietary sugar disrupts immune-mediated protection from metabolic syndrome. Cell185, 3501–3519 (2022). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR48] 48.Fu, A. et al. Tumor-resident intracellular microbiota promotes metastatic colonization in breast cancer. Cell185, 1356–1372 (2022). [DOI] [PubMed] [Google Scholar]

[CR49] 49.Du, D. et al. Differences in glucose homeostasis and islet injury among diverse mice strains post acute pancreatitis. Biochem. Biophys. Res. Commun.708, 149780 (2024). [DOI] [PubMed] [Google Scholar]

[CR50] 50.Barupal, D. K. & Fiehn, O. Chemical similarity enrichment analysis (ChemRICH) as alternative to biochemical pathway mapping for metabolomic datasets. Sci. Rep.7, 14567 (2017). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR51] 51.Pang, Z. et al. MetaboAnalyst 6.0: towards a unified platform for metabolomics data processing, analysis and interpretation. Nucleic. Acids. Res. 52, W398–W406 (2024). [DOI] [PMC free article] [PubMed]

[CR52] 52.Li, C. et al. Multiomic analysis of different horse breeds reveals that gut microbial butyrate enhances racehorse athletic performance. npj Biofilms Microbomes11, 87 (2025). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR53] 53.Lu, Y. et al. HDL inhibits pancreatic acinar cell NLRP3 inflammasome activation and protect against acinar cell pyroptosis in acute pancreatitis. Int. Immunopharmacol.125, 110950 (2023). [DOI] [PubMed] [Google Scholar]

PERMALINK

Trehalose ameliorates severe acute pancreatitis by modulating gut microbial metabolism

Haibin Hao

Deren Du

Hong Lin

Lu Ke

Aikun Fu

Chongli Shi

Wei Li

Yuanzhen Li

Gaohuan Hou

Lianglan Li

Yuxiu Liu

Shengwen Shao

Weiqin Li

Zhihui Tong

Abstract

Introduction

Results

Bacterial depletion ameliorates pancreatic injury and the inflammatory response in SAP

Fig. 1. Bacterial depletion ameliorates pancreatic injury and the inflammatory response in SAP.

Bacterial depletion reverses the SAP-induced imbalance in gut microbial metabolism

Fig. 2. Bacterial depletion reverses the SAP-induced imbalance in gut microbial metabolism.

Trehalose ameliorates the severity of severe acute pancreatitis

Fig. 3. Trehalose ameliorates the severity of severe acute pancreatitis.

Trehalose modulates gut microbial metabolism homeostasis in SAP

Fig. 4. Trehalose modulates gut microbial metabolism homeostasis in SAP.

Trehalose ameliorates SAP in a gut microbiota-dependent manner

Fig. 5. Trehalose ameliorates SAP in a gut microbiota-dependent manner.

Galactose metabolism and Muribaculaceae are key factors in the trehalose-induced “microbial metabolism-gut-pancreatic axis”

Fig. 6. Galactose metabolism and Muribaculaceae are key factors in the trehalose-induced “microbial metabolism-gut-pancreatic axis”.

Trehalose reduces macrophage infiltration and caspase-3-mediated apoptosis in the pancreas

Fig. 7. Trehalose reduces macrophage infiltration in the pancreas.

Fig. 8. Trehalose reduces caspase-3-mediated apoptosis in the pancreas.

Metagenomic and metatranscriptomic alterations of the gut microbiota after ATBx and trehalose treatment

Fig. 9. Metagenomic and Metatranscriptomic analysis of gut microbiota after ATBx treatment.

Discussion

Methods

Animal experiments

Severe acute pancreatitis model

Histopathological evaluation

Faecal microbial transplantation (FMT)

16S rRNA gene sequencing analysis

Metabolomic analysis

Metagenomic and metatranscriptomic analyses

Cytokine analysis

Lipid analysis

Immunohistochemical analysis

Immunofluorescence staining

Western blotting analysis

Statistical analysis

Supplementary information

Acknowledgements

Author contributions

Data availability

Competing interests

Footnotes

Contributor Information

Supplementary information

References

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

Similar articles

Cited by other articles

Links to NCBI Databases