Changes in pancreatic and ileal flora and related relationships in experimental acute pancreatitis

doi:10.21203/rs.3.rs-2627448/v1

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Changes in pancreatic and ileal flora and related relationships in experimental acute pancreatitis

https://doi.org/10.21203/rs.3.rs-2627448/v1

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Background/Objectives: Gut microbiota dysbiosis is a complication of acute pancreatitis (AP). However, the composition of the pancreatic and ileal microbiota and their relationship during acute pancreatitis remain unknown.

Methods: AP was induced in mice using three modeling methods, Caerulein (CAE), Caerulein+lipopolysaccharide (CAE+LPS) and L-arginine (ARG). Pancreas and ileum were collected for histological study and bacterial 16S rRNA gene sequencing to investigate the changes in the pancreatic and ileal flora under different inductions and their relationships. Blood samples were tested for amylase, lipase, and inflammatory markers, and histological investigations were done to assess pancreatic and ileal pathological damage.

Results: All three modeling techniques led to inflammation and AP and ileal damage. Rarefaction and Shannon indices revealed that the pancreas and ileum of AP mice had higher levels of microbial diversity. Principal coordinate analysis (PCoA) and non-metric multidimensional scaling (NMDS) analysis showed microbial structural segregation in both the AP and control groups in the pancreas and ileum. In the three AP groups, there was microbial structural segregation between the ARG and the two CAE groups (CAE, CAE+LPS). Taxonomic analysis at the genus level showed a significant increase in the relative abundance of Muribaculaceae and a decrease in the relative abundance of Dietzia in the pancreas and ileum of AP mice. The same finding was found for linear discriminant analysis of effect size (LEfSe) at the operational taxonomic unit (OTU) level. In addition, the pancreas and ileum of both CAE groups were enriched with Roseburia, whereas the pancreas of the ARG group was enriched with Escherichia-Shigella. The abundance of Muribaculaceae and Dietzia in the pancreas is associated with that in the ileum, according to Spearman correlation analysis of the pancreatic and ileal microbiota.

Conclusions: These results showed that when AP was induced, caerulein and L-arginine differentially affected the pancreatic and ileal microbiota.

acute pancreatitis

pancreatic microbiota

ileal microbiota

Muribaculaceae

Dietzia

Acute pancreatitis (AP) is a common and urgent gastrointestinal disorder, which has a rising prevalence worldwide and is a financial burden. It is characterized by premature activation of digestive zymogens within the pancreatic acinar cells and pancreatic self-digestion^[1]. About 70–80% of patients develop mild acute pancreatitis (MAP), and about 20–30% develop severe acute pancreatitis (SAP) that has systemic inflammatory response syndrome(SIRS) and multiple organ failure (MOF)^[2].

Many clinical and animal pieces of evidence suggest that gut dysfunction, including gut barrier destruction and gut microbiota dysbiosis, is a crucial event in the AP. In detail, gut barrier dysfunction during AP is associated with an unfavorable prognosis^{[3, 4]}; the gut microbiota is often significantly altered in patients with SAP, and dysbiosis of gut microbiota can induce intestinal mucosal immune dysfunction, increase intestinal permeability and promote intestinal bacterial translocation ^{[5, 6]}. Moreover, the small bowel seems to be the major source of enteral bacteria in infected pancreatic necrosis, while not the colon^[7].

Many studies applied bacteria culture or qPCR to identify gut bacteria, such as Escherichia coli, Enterobacter aerogenes, and Bacillus proteus could translate to the pancreas during AP^[8–10]. Bacterial translocation into the pancreas during SAP has been closely associated with pancreatic infection and ultimately leads to serious local complications such as pancreatic necrosis and pancreatic inflammation. Recent studies have shown that intestinal flora disorders lead to disruption of iron homeostasis in vivo and that intestinal flora metabolites induce iron death in intestinal epithelial cells promoting intestinal flora translocation, which in turn leads to the development of SAP^{[11, 12]}. However, few studies have looked into the comprehensive bacterial spectrum, which is translated from the gut to the pancreas during AP.

Thus, the present study is the first to elucidate the ileal and pancreatic microbial changes during AP with bacterial 16S rRNA gene sequencing, compares the different effects on microbiota between caerulein and L-arginine induced AP, and explores the relationship between pancreatic and ileal microbiota in order to find the bacteria that might migrate from the intestine to the pancreas and are closely related to the occurrence and development of AP.

2.1. Mice experimental design

Male C57BL/6 mice weighing 20 to 22 grams were purchased from Shanghai SLAC Laboratory Animal Co.Ltd (Shanghai, China). All mice were housed under specific pathogen-free (SPF) conditions with a room temperature of 23 ± 2°C with a 12-hour shift of the light-dark cycle and had free access to water and mouse chow. All the animal experiments were performed in accordance with the guidelines of the Animal Care and Use Committee of Shanghai Jiao Tong University. All procedures were approved by the Animal Ethics Committee of Shanghai General Hospital.

The Mice were randomly divided into four groups, including healthy control (CON), caerulein-induced pancreatitis (CAE), caerulein and LPS induced pancreatitis (CAE + LPS), and L-arginine-induced pancreatitis (ARG). There were ten mice in the CON group and five mice in each of the other three pancreatitis groups. For the CAE + LPS group, mice received ten-hourly i.p. injections of 100 µg/kg caerulein and one intraperitoneal injection of LPS (5mg/kg) immediately after the final injection of caerulein. For L-arginine-induced pancreatitis, mice received two-hourly intraperitoneal(i.p.) injections of L-arginine hydrochloride (8%, pH = 7.0, 4.5g/kg).

2.2. Histopathology

Pancreatic and ileal specimens were fixed with 4% paraformaldehyde, dehydrated, embedded with paraffin, cut into 4µm sections, and stained with hematoxylin and eosin (H&E). The morphologic evaluation was performed by a light microscope (Leica, Germany) at a magnification of ×200. The histopathological changes to the pancreas, including pancreatic edema, acinar cell necrosis, hemorrhage, and inflammation, were evaluated according to the criteria of Schmidt^[13], while the pathological damage to the ileum, including ileal mucosal damage, inflammation, and hemorrhage/congestion were scored according to Chiu's standard^[14].

2.3. Serum and Plasma Biochemistry

Blood samples from each group were collected and centrifuged at 3000rpm for 15min at 4°C. The serum levels of amylase were determined by using commercial kits in the Advia 2400 chemistry system according to the manufacturer’s protocol (Siemens, German). The serum levels of TNF-α and IL-1β, lipase were measured by enzyme-linked immunosorbent assay (ELISA) (MultiSciences Biotech, China) according to the manufacturer’s protocols.

2.4. Western blotting

Epizyme Biotech, China's radioimmunoprecipitation assay (RIPA) lysis buffer with 1% protease inhibitor was used to lyse pancreas and ileum tissues (Epizyme Biotech, China). The homogenates were centrifuged at 10,000 g for 10 minutes at 4°C after being allowed to sit on ice for an hour. The supernatants were then collected. SDS loading buffer (Yeason, China) was combined with the extracts before the mixture was heated at 100°C for 10 minutes. Using a PAGE gel rapid preparation kit (Epizyme Biotech, China), ten microliters of the solution were put into a 10% SDS-PAGE gel and electrophoresed before being transferred to PVDF membranes (Millipore, USA). The membranes were treated with the following antibodies (1:1000): tubulin (ABclonal, China); claudin 1 (ABclonal, China) for 1 hour at room temperature after blocking with 3% bovine serum albumin (BSA) (YEASEN, China). The membranes were washed three times with Tris Buffered Saline with Tween-20 (TBST) the next day before being incubated for one hour at room temperature with peroxidase-conjugated goat anti-rabbit IgG(H1L) (Yeason, China). Once more, TBST was used to cleanse the membranes three times. Horseradish peroxidase (HRP) substrate peroxide solution (Epizyme Biotech, China) and Amersham 600 images were used to detect protein bands (General Electric, USA). ImageJ software was used to calculate the density of each band.

2.5. DNA extraction PCR amplification and sequencing of bacteria in the pancreas and ileum

Pancreas and ileum tissues were soaked in 20ul of 20mg/ml protease solution and 300ul of PBS solution at 60°C overnight. The samples were placed in a 2 ml screw-cap tube containing 1g of glass beads and suspended in 790 l of sterile lysis buffer (4M guanidine thiocyanate; 10% N-lauroyl sarcosine; 5% N-lauroyl sarcosine-0.1 M phosphate buffer, pH 8.0). (0.1mm BioSpec Products, Inc., USA). After vigorous vortexing, this mixture was incubated for an hour at 70°C while being forcefully bead beaten for 10 minutes. The E.Z.N.A.® Stool DNA Kit (Omega Bio-tek, Inc., GA) was used to extract DNA in accordance with the manufacturer's instructions for bacterial DNA extraction, except for lysis stages, and DNA was kept at -20°C for future analysis.

The bacterial universal primers F1 and R2 (5'- CCTACGGGNGGCWGCAG-3' and 5'-GACTACHVGGGTATCTAATCC-3'), which correspond to locations 341 to 805 in the Escherichia coli 16S rRNA gene, were used to amplify the V3-V4 region of the bacterial 16S ribosomal RNA gene from each sample. The following software was used to execute PCR reactions in an EasyCycler 96 PCR equipment (Analytik Jena Corp., AG): Denaturation takes place for 3 min at 95°C, then there are 21 cycles of denaturation lasting 0.5 min at 94°C, annealing lasting 0.5 min at 58°C, and elongation lasting 0.5 min at 72°C, with a final extension lasting 5 min at 72°C.

According to the manufacturer's instructions, Shanghai Mobio Biomedical Technology Co. Ltd. used the Miseq platform (Illumina Inc., USA) to index and mix the products from several samples in similar amounts for sequencing.

2.6. Bioinformatics Analysis of sequencing data

Using USEARCH (version 11.0.667), clean data was retrieved from raw data according to the following standards: (i) With no mismatches, sequences from each sample were retrieved using each index. (ii) Sequences with an overlap of under 16 base pairs were eliminated. (iii) The overlap error rate of more than 0.1 was eliminated. (iv) Sequences with a merge length of less than 400 bp were deleted. According to the UPARSE OTU analysis process, quality-filtered sequences were grouped into distinct sequences and sorted in order of decreasing abundance to determine representative sequences; singletons were removed in this phase. Once chimeric sequences were deleted, Operational Taxonomic Units (OTUs) were categorised using UPARSE (version 7.1; available at http://drive5.com/uparse/) and annotated using the SILVA reference database (SSU138). Mothur v1.42.1 was used to evaluate the Alpha diversity metrics (ACE estimator, Chao 1 estimator, Shannon-Wiener diversity index, and Simpson diversity index). To determine whether there were significant differences between the two groups, the nonparametric Mann-Whitney U test was used. A nonparametric Kruskal-Wallis test was used to compare multiple groups. QIIME was used to compute Bray-Curtis, weighted, and unweighted UniFrac dissimilarity. R (version 3.6.0) package vegan 2.5-7 was used to generate principal coordinate analysis (PCoA) plots and PERMANOVA, which were used to test for statistical significance between groups using 10,000 permutations. To detect taxa with differential abundance among groups, the linear discriminant analysis (LDA) effect size (LEfSe) method was used (lefse 1.1, https://github.com/SegataLab/lefse). Based on 16S rRNA gene sequences, PICRUSt2 v2.4.1 (https://github.com/picrust/picrust2/wiki) was used to predict functional abundances.

2.7. Statistical Analysis

Data were presented as mean ± standard deviation (SD). Student’s t-test, Mann-Whitney test, and Spearman correlation test were performed using SPSS 19.0 software, and a p-value of < 0.05 was considered statistically significant.

3.1. Caerulein, Caerulein + LPS and L-Arginine induced AP in mice

The three AP models were established by using L-arginine, caerulein, and caerulein + LPS. Pathological pancreatic damages and inflammation were found in all the three AP mice, presenting with higher scores of edema, hemorrhage, acinar necrosis, and inflammatory cell infiltration than the control group (Fig. 1A). And histopathological injury in the pancreas of the CAE + LPS group and ARG group was more aggravated compared with that of the CAE group (Fig. 1A). The AP groups exhibited significantly increased serum amylase and lipase levels compared with the CON group (Fig. 1B, C). Proinflammatory cytokines IL-1β and TNF-α in the serum were significantly increased in the AP groups than in the control group (Fig. 1D, E), suggesting that AP groups had higher systemic inflammation. Except for the damage and inflammation in the pancreas, AP also induced intestinal injury. Ileal pathological changes, including ileal mucosal damage, inflammation, and hemorrhage/congestion, showed the three AP groups aggravate ileal injury (Fig. 1F). In addition, AP induction decreased the expression of claudin-1 in the terminal ileum (Fig. 1G), indicating that AP mice had gut barrier dysfunction. The CAE group had less intestinal barrier damage than the other two groups, which was likely owing to the severity difference.

3.2. AP mice had a more abundant microbiota in the pancreas and ileum

A total of 1117034 usable sequences were obtained from 50 samples using Illumina high-throughput sequencing technology, with an average of 22341 sequences per sample. From these, 731 OTUs were generated at a 97% similar level. The rarefaction curves reached a plateau with the current sequencing, and the Shannon diversity estimates of all the samples were stable (Fig. S1), indicating that most diversity had already been discovered. The alpha diversities (richness and diversity) of the pancreatic and ileal microflora were not different in the same group (Fig. 2). The three AP groups had significantly higher levels of Shannon indices, Chao1, Ace indices, and OTU numbers than the control group (Fig. 2). All the results suggested that AP mice had a more abundant microbiota in both the pancreas and ileum.

3.3. AP changed pancreatic microbiota

3.3.1. Differences in microbiome compositions in the pancreas

Beta diversity analysis was performed to evaluate dissimilarities in pancreatic microbial communities among groups using principal coordinates analysis (PCoA) and non-metric multidimensional scaling (NMDS) analysis based on Bray-Curtis distances (Fig. 3A, B). Significant segregation was found between the CON group and AP groups according to the PC1, which accounted for 44.35% in PCoA (Fig. 3A) and NMDS (Fig. 3B) of the total variations of the pancreatic microbiota. To further elucidate the differences in microbial structure, we calculated the relative abundance of bacteria. The microbiota structure at the phylum and genus levels was performed (Fig. 3C, D). The pancreatic microbiota was dominated by Proteobacteria in the CON group, followed by Bacteroidota, Firmicutes, and Actinobacteriota with proportions of 36.84%, 24.41%, 19.44% and 15.70%, respectively. Compared with the CON group, increases in Firmicutes and Bacteroidota abundance and decreases in Proteobacteria, Actinobacteriota, and Unassigned_unclassified abundance significantly reduced the similarities of the microbiome among the AP groups (Fig. 3C). At the genus level, the AP groups had a higher abundance of Muribaculaceae, Lachnosporaceae, Akkermansia, and Bacteroides (p < 0.05, respectively). The abundance of Acinetobacter, Dietzia, Halomonas, and Aliidiomarina in the CON group was significantly higher than in the AP groups (p < 0.05, respectively) (Fig. 3D).

3.3.2. Differences in the microbiota of three AP groups in the pancreas

According to LEfSe analysis, the CON and AP groups showed the greatest differences in microbial structure in the pancreas at the OTU level, and then the results of the three groups were pooled, and heat map analysis was done (Fig. 4). Among these observed OTUs, 59 OTUs were more abundant in the CAE group than the CON group, which belonged to the genera of Muribaculaceae, Lachnospiraceae_NK4A136_group, Bacteroides, Akkermansia, and so on (LDA > 3, p < 0.05). In comparison, the pancreas of mice in the CAE + LPS group was enriched with 58 OTUs, which belonged to the genera similar to the CAE group. In addition, 39 OTUs significantly with greater abundances of species, including Muribaculaceae, Muribaculum, Bacteroides, Delftia, Lachnospiraceae_NK4A136_group, were observed in the pancreas of the ARG group than that in the CON group (LDA > 3, p < 0.05). And 14 OTUs were richer in the CON group than that in the AP groups, which belonged to the genera of Corynebacterium, Pseudomonas, Caulobacter, Lawsonella, and so on (LDA > 3, p < 0.05) (Fig. S2 A-C).

3.3.3. Functional changes of three AP groups in the pancreas

To characterize the functional alterations in the pancreatic and ileal microbiota of healthy and AP mice, we predicted the functional composition profiles using PICRUSt according to the KEGG database. A comparison between the CON and CAE groups showed that 28 KEGG pathways were enriched in the CON group, including Geraniol degradation, Synthesis and degradation of ketone bodies, Fatty acid degradation, etc.; and 29 pathways were significantly enriched in the CAE group, such as Biosynthesis of ansamycins, mRNA surveillance pathway, etc. (Fig. S3D) (LDA > 4, p < 0.05). The pathways involved in microbial metabolism in the pancreas in the CAE + LPS group were similar to those in the CAE group (Fig. S3E) (LDA > 4, p < 0.05). A comparison between the CON and ARG groups showed that the Metabolism of xenobiotics by cytochrome P450 was significantly enriched in the CON group, and two KEGG pathways, including Other glycan degradation and Naphthalene degradation, were enriched in the ARG group (Fig. 4, Fig. S3F).

3.4. AP changed ileal microbiota

3.4.1 Differences in microbiome compositions in the ileum

Microbiota in the ileum was also modulated by AP. PCoA analysis based on Bray-Curtis distance of ileal microbiota data showed that the first principal component accounting for 28.91% of the total variance separated the control group and the three AP groups (Fig. 5A). The same results were also shown by NMDS analysis (Fig. 5B). The microbiota structure at the phylum and genus levels in the ileum was performed in Fig. 5C and 5D. The ileal microbiota was dominated by Bacteroidota in the CON group, followed by Firmicutes, Proteobacteria, and Verrucomicrobiota. At the phylum level, we found that Deferribacterota, Actinobacteriota, and Campilobacterota were significantly lower in the AP groups than in the CON group, while Verrucomicrobiota was higher (Fig. 5C). At the genus level, the AP groups had a higher abundance of Muribaculum, Oscillospiraceae_unclassified, and Bacteroides(p < 0.05, respectively). The abundance of Helicobacter and Dietzia in the CON group was significantly higher than in the AP groups(p < 0.05, respectively) (Fig. 5D).

3.4.2 Differences in the microbiota of three AP groups in the ileum

The largest differences in microbial structure between the CON and AP groups at the OTU level in the ileum were shown according to LEfSe analysis, performing the same thermogram analysis as for the pancreas (Fig. 6). Among these observed OTUs, 51 OTUs were more abundant in the CAE group than the CON group, which belonged to the genera of Akkermansia, Muribaculaceae, Bacteroides, and so on (LDA > 3, p < 0.05). While the ileum of mice in the CAE + LPS group was enriched with 55 OTUs, which belonged to the genera of Lachnospiraceae_NK4A136_group, Alloprevotella, Bacteroides, etc. (LDA > 3, p < 0.05). In addition, 26 OTUs significantly with greater abundances of species, including Muribaculaceae, Muribaculum, Bacteroides, etc., were observed in the ileum of the ARG group than that in the CON group (LDA > 3, p < 0.05). And 15 OTUs were richer in the CON group than that in the AP groups, which belonged to the genera of Aliidiomarina, Muribaculaceae, Lactobacillus, Lachnospiraceae_NK4A136_group, and so on (LDA > 3, p < 0.05) (Fig. 6, Fig. S3 A-C).

3.4.3 Functional changes of three AP groups in the ileum

We also compared metabolism pathways in the ileum of the CON and AP groups. Naphthalene degradation and Butanoate metabolism were significantly higher in the CAE group compared to the control group, while Isoflavonoid biosynthesis and Nicotinate and nicotinamide metabolism were significantly higher in the control group compared the CAE group (Fig. S3D). In the LPS group, Carbon fixation in photosynthetic organisms and Cysteine and methionine metabolism were significantly enriched, and Lipid metabolism, Limonene and pinene degradation, and Linoleic acid metabolism were enriched in the control group (Fig. S3E). Compared with the control group, the ARG group was enriched in Naphthalene degradation and Retinol metabolism pathway (Fig. S3F).

3.5 The three AP mice models had distinct pancreatic and ileal microbiota

The three AP mice had different pancreatic and ileal microbiota. Microbial diversity analysis in the pancreas showed that the CAE group had the highest microbial diversity, and the microbial diversity in the ARG group was similar to that of the CAE + LPS group (Fig. 2, Fig. S1). PCoA and NMDS analyses showed that the overall pancreatic microbial structure of CAE and CAE + LPS groups were different from that of the ARG group according to PC2, which accounted for 12.66% of the total variance (Fig. 3A, B). Compared with the ARG group, the abundance of Roseburia, Oscillospiraceae_unclassified, Anaerotruncus, and so on were enriched, and Massilia was decreased in the CAE group (Fig. 7A); the abundance of Erysipelatoclostridium and Escherichia − Shigella was decreased in the pancreas of the LPS group (Fig. 7B). The proportions of Alloprevotella, Prevotellaceae_UCG − 001 and Rikenellaceae_RC9_gut_group were increased, and the proportion of Colidextribacter was decreased in mice of the CAE + LPS group compared to that in the CAE group (Fig. 7C).

At the same time, in the ileal microbiota, microbial diversity analysis in the ileal showed that the microbiota α diversity in the CAE group and CAE + LPS group were higher than that in the ARG group, and the level of the ARG group was close to that of the control group (Fig. 2, Fig. S1). β-diversity analysis showed that the compositions of bacteria in the CAE group and the CAE + LPS group were similar and were deviated from the ARG group slightly (Adonis analysis, P = 0.2422, P = 0.0072, respectively) according to PC2, which accounted for 16.83% of the total variance (Fig. 5A, B). Compared with the ARG group, the CAE group had an increase in Roseburia, Parabacteroides and Desulfovibrio (Fig. 7D), while the LPS group had an increase in Lachnospiraceae_NK4A136_group, Oscillospiraceae_unclassified, and Alloprevotella, and decrease of Lactobacillus (Fig. 7F). Compared with the CAE group, the abundance of Alloprevotella and Blautia in the CAE + LPS group increased significantly, and the abundance of Dubosiella, Parabacteroides, and Desulfovibrio were decreased significantly (Fig. 7E). All these results suggested that the three AP modeling methods affected the microbiota in both pancreas and ileum (Fig. 3–7).

3.6 Changed pancreatic microbiota was associated with the ileal microbiota.

To further explore the relationship between the pancreatic microbiota and the ileal microbiota of each individual, we performed a correlation analysis between the greatest differences in microbial structure in the pancreas and ileum obtained from the previous LefSe analysis, and the results are shown in Table 1. We found that 14 OTUs were significantly correlated in the pancreas and ileum when restricting rho to > 0.8, and these discovered OTUs belong to Muribaculaceae, Halomonas, Anaeroplasma, Lachnospiraceae_NK4A136_group, Rikenellaceae_RC9_gut_group, Dietzia, Aliidiomarina, Delftia, Lachnospiraceae_unclassified. It was demonstrated that these bacteria were not only maximally different between the CON and AP groups, but also significantly correlated in the pancreas and ileum.

In addition, we performed the Spearman correlation between the relative abundance of the changed pancreatic microbiota and those of the corresponding bacteria in the ileal with or without induction of AP in mice. We discovered that in the control mice, the microbiota with a significant correlation in pancreas and ileum included Rikenellaceae_RC9_gut_group, Rhodococcus, Prevotellaceae_UCG − 001, Odoribacter, Muribaculum, Lachnospiraceae_uncultured, Lachnospiraceae_ASF356, Anaerotruncus, Anaeroplasma, and so on. Most of these bacteria showed an upward trend after induction of AP in mice. However, after AP induction, the genera with a significant correlation between pancreas and ileum included Roseburia, Parabacteroides, Marvinbryantia, Lachnospiraceae_NK4A136_group, Erysipelatoclostridium, Desulfovibrio, Delftia, Comamonas, Blautia, Anaerotruncus, Anaeroplasma, etc. (Fig. 8). The results showed that healthy and AP mice had different relationships between microbiota from the pancreas and ileum except for Anaerotruncus and Anaeroplasma. In addition, these two bacteria were more abundant in the ileum and pancreas during AP.

Although AP exhibits abnormal intestinal permeability and bacterial translocation, the comprehensive bacteria translating from gut to pancreas is not clearly understood. Our 16S rRNA gene sequencing-based study in mice confirmed that 1) In the three mice models, AP induced more kinds of bacteria to migrate to the pancreas, including bacteria belonging to Muribaculaceae, while reducing the relative abundance of bacteria such as Dietzia in the pancreas. These bacteria were also changed with the same trend in the ileum. 2) Caerulein and L-arginine differentially disturbed the pancreatic and ileal microbiota when inducing AP. In the caerulein-induced AP mice, Roseburia was enriched in both pancreas and ileum; and in the L-arginine-induced AP mice, Escherichia-Shigella expanded in the pancreas.

In the present study, caerulein, caerulein + LPS and L-arginine were used to induce AP and ileal injury and inflammation. We found that the bacterial diversity in the pancreas and ileum of mice after induction of AP was significantly higher than that in the control group. Furthermore, previous studies found that Escherichia–Shigella, Enterococcus and other opportunistic pathogens were overrepresented in AP, whereas potentially beneficial bacteria Blautia, Lachnospiraceae and Ruminococcaceae were enriched in the intestinal microbiota of the healthy control ^{[6, 15–17]}, but our study with 16S rRNA gene sequencing identified some different bacteria in the pancreas and ileum. Compared to the control group, Muribaculaceae, Akkermansia and Parabacteroides were increased, and Dietzia was decreased in both the pancreas and the ileum. Muribaculaceae is a newly discovered strictly anaerobic gram-negative bacillus, and it is involved in the metabolism of fatty acids like propionic acid^[18]. Now, it is controversial about the function of this bacteria, some studies think it is pathogenic and linked to systemic inflammation^{[19, 20]}, but other studies find it is associated with reduction of gut inflammation^[21–24]. In this study, Muribaculaceae in the pancreas and ileum was enhanced during AP, suggesting that it might be related to the pathology of AP. Akkermansia is a commensal bacterium that colonizes the mucosal layer of the intestine and could improve host metabolic dysfunction and reduce inflammation response; thus it is considered a promising probiotic candidate^{[25, 26]}. Parabacteroides is reported to produce acetate and ameliorate heparanase-exacerbated acute pancreatitis by reducing neutrophil infiltration^{[27, 28]}. Akkermansia and Parabacteroides were increased in the pancreas and ileum when inducing AP, and this might be due to the protective response of the host against the modeling drug. The Gram-positive strain Dietzia can grow at low temperatures and is widely distributed in the natural environment. It has been reported to synthesize carotenoids, as well as degrade a broad range of n-alkanes^[29–31]. Bifidobacterium was only reduced in the ileum of the three AP groups than in the healthy control. In the previous study, it had been used with enteral nutrition to treat SAP^[32].

The mechanisms of AP induced by caerulein and L-arginine are different^{[33, 34]}, but it is still unclear whether they have different effects on gut microbiota. This study investigated the effects of different AP induction methods on the microbiota in the gut and pancreas for the first time. According to an unsupervised multivariate analysis, the overall bacterial structure of caerulein groups (CAE, CAE + LPS) and L-arginine group were separated in the pancreas and ileum. Moreover, Roseburia was enriched in the two caerulein groups in the pancreas and/or ileum, while Escherichia-Shigella expanded in the pancreas of the L-arginine group. Roseburia can prevent intestinal inflammation and regulate barrier homeostasis through the metabolites butyrate and flagellin^[35]. An increase in Roseburia might protect the host from caerulein induced AP at the initial stage of the disease. In contrast, Escherichia-Shigella can aggravate necrotizing pancreatitis in other studies. KEGG pathway analysis showed that the L-Arg group's pancreas had increased metabolic pathways, primarily through Other glycan degradation and Naphthalene degradation. The genus Anaplasma was abundant in the pancreas of the L-Arg group, while the Bacteroidetes phylum is known for its ability to degrade a variety of complex carbohydrates, a result that corresponds to an increase in the metabolic pathway Other glycan degradation^[36]. Upon further investigation, we found that the CAE and CAE + LPS groups were involved in comparable pathways in the pancreas, confirming the previous flora structure. This result suggests that the microbiota and its functional composition are similar due to the similarity of modeling approaches. Combined with the results of this study, it showed that it might be involved in the L-arginine induced necrotizing AP^[37]. Altogether, although the disruption of the gut and pancreatic microbiota during the onset of AP, there may still be a compensatory increase in the abundance and translocation of more beneficial bacteria, such as Roseburia, in the caerulein induced AP than in the L-arginine induced necrotizing AP.

Although previous researches have shown that AP disrupts the gut microbiota in humans and animal models, few studies have looked into the correlation of microbiota in the pancreas and ileum. In this study, Spearman correlation analysis between pancreatic and ileal microbiota revealed the abundances of OTU44 (Muribaculaceae), OTU117 (Halomonas), and OTU27 (Anaeroplasma), etc. in the pancreas were related to that in the ileum. These indicated that these bacteria were likely to pass through the intestinal barrier in some way and enter the pancreas from the intestine. Moreover, we discovered that AP could cause different bacterial translocation so that bacteria with significant correlation in the pancreas and ileum of healthy mice and AP mice were different.

There are still several limitations to this study that need to be addressed. Firstly, the small sample size resulted in significant between-group differences. Secondly, the present study was only an association study and failed to directly prove the existence of microbiota translocation from the ileum to the pancreas.

In conclusion, we demonstrated that AP induced an imbalance of pancreatic microbiota, which was closely related to the ileal microbiota, and Cerulein and L-arginine acted on different pancreatic and ileal bacteria. Although the causal relationship and mechanism between these bacteria and AP need to be proved, we have found the microbial markers of AP and can use them as therapeutic targets in the future.

Ethics approval and consent to participate

This study was approved by the ethics committee of Shanghai General Hospital (approval No.2022KY096). The studies involving animals partially in compliance with the ARRIVE guidelines.

Consent for publication

Not Applicable.

Availability of data and materials

The 16S rRNA sequence data generated in this study have been deposited in the Sequence Read Archive database under accession number PRJNA842514. The URL is as follows: https://trace.ncbi.nlm.nih.gov/Traces/sra/. Now the data has been uploaded but not been public. The data will not be available until paper being accepted. The reviewer’s link is as follows: https://dataview.ncbi.nlm.nih.gov/object/PRJNA842514?reviewer=n6if6of2tctjg4a08v1bul2ib8.

Competing interests

All authors claimed no conflicts of interests.

Funding

This work was supported by the Shanghai Natural Science Foundation Project (Grant No.22ZR1453500), the Science and Technology Project of Jiading Hospital, Shanghai General Hospital (Grant No. 202135A) and the fifth batch of medical key disciplines in Jiading District, Shanghai (2020-jdyxzdxk-15).

Author’s contributions

All authors were involved in patients' enrollment, performing the study, acquisition of data and interpretation of study results. Meng-Yan Cui and Zhen-Yu Cui drafted the manuscript. Ying-Ying Lu was involved in the study design and critical revision of the manuscript. All authors approved the final version of the manuscript, including the authorship list.

Acknowledgements

The authors would like to acknowledge Chen H for kind support and skillful technical assistance. Thanks to the Shanghai Natural Science Foundation Project (Grant No.22ZR1453500), the Science and Technology Project of Jiading Hospital, Shanghai General Hospital (Grant No. 202135A) and The fifth batch of medical key disciplines in Jiading District, Shanghai (2020-jdyxzdxk-15).

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Table 1

correlation analysis between the greatest differences in microbial structure in the pancreas and ileum
	OTU	Rho	p_value
1	OTU44 (Muribaculaceae)	0.934755574	༜0.001
2	OTU117 (Halomonas)	0.903396145	༜0.001
3	OTU27 (Anaeroplasma)	0.894354839	༜0.001
4	OTU8 (Anaerotruncus)	0.890898251	༜0.001
5	OTU67 (Muribaculaceae)	0.884818826	༜0.001
6	OTU3 (Lachnospiraceae_NK4A136_group)	0.88152809	༜0.001
7	OTU55 (Rikenellaceae_RC9_gut_group)	0.875320249	༜0.001
8	OTU41 (Muribaculaceae)	0.870283019	༜0.001
9	OTU35(Lachnospiraceae_NK4A136_group)	0.845194922	༜0.001
10	OTU20 (Dietzia)	0.831554236	༜0.001
11	OTU189 (Aliidiomarina)	0.825593033	༜0.001
12	OTU50 (Delftia)	0.809621838	༜0.001
13	OTU43 (Lachnospiraceae_unclassified)	0.804835266	༜0.001
14	OTU88 (Muribaculaceae)	0.802774593	༜0.001
Note: The Rho representative spearman correlation coefficient, and it is taken to be greater than 0.8.

No competing interests reported.

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Changes in pancreatic and ileal flora and related relationships in experimental acute pancreatitis

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Abstract

Figures

1. Introduction

2. Methods

2.1. Mice experimental design

2.2. Histopathology

2.3. Serum and Plasma Biochemistry

2.4. Western blotting

2.5. DNA extraction PCR amplification and sequencing of bacteria in the pancreas and ileum

2.6. Bioinformatics Analysis of sequencing data

2.7. Statistical Analysis

3. Results

3.1. Caerulein, Caerulein + LPS and L-Arginine induced AP in mice

3.2. AP mice had a more abundant microbiota in the pancreas and ileum

3.3. AP changed pancreatic microbiota

3.3.1. Differences in microbiome compositions in the pancreas

3.3.2. Differences in the microbiota of three AP groups in the pancreas

3.3.3. Functional changes of three AP groups in the pancreas

3.4. AP changed ileal microbiota

3.4.1 Differences in microbiome compositions in the ileum

3.4.2 Differences in the microbiota of three AP groups in the ileum

3.4.3 Functional changes of three AP groups in the ileum

3.5 The three AP mice models had distinct pancreatic and ileal microbiota

3.6 Changed pancreatic microbiota was associated with the ileal microbiota.

4. Discussion

Declarations

References

Tables

Additional Declarations

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