Abstract

Objective

   Carboxymethylcellulose (CMC), one of the most common emulsifiers used
   in the food industry, has been reported to promote chronic inflammatory
   diseases, but its impact on acute inflammatory diseases, e.g., acute
   pancreatitis (AP), remains unclear. This study investigates the
   detrimental effects of CMC on AP and the potential for mitigation
   through Akkermansia muciniphila or butyrate supplementation.

Design

   C57BL/6 mice were given pure water or CMC solution (1%) for 4 weeks and
   then subjected to caerulein-induced AP. The pancreas, colon, and blood
   were sampled for molecular and immune parameters associated with AP
   severity. Gut microbiota composition was assessed using 16S rRNA gene
   amplicon sequencing. Fecal microbiota transplantation (FMT) was used to
   illustrate gut microbiota’s role in mediating the effects of CMC on
   host mice. Additional investigations included single-cell RNA
   sequencing, monocytes-specific C/EBPδ knockdown, LPS blocking, fecal
   short-chain fatty acids (SCFAs) quantification, and Akkermansia
   muciniphila or butyrate supplementation. Finally, the gut microbiota of
   AP patients with different severity was analyzed.

Results

   CMC exacerbated AP with gut dysbiosis. FMT from CMC-fed mice
   transferred such adverse effects to recipient mice, while single-cell
   analysis showed an increase in classical monocytes in blood.
   LPS-stimulated C/EBPδ, caused by an impaired gut barrier, drives
   monocytes towards classical phenotype. LPS antagonist (eritoran),
   Akkermansia muciniphila or butyrate supplementation ameliorates
   CMC-induced AP exacerbation. Fecal Akkermansia muciniphila abundance
   was negatively correlated with AP severity in patients.

Conclusions

   This study reveals the detrimental impact of CMC on AP due to gut
   dysbiosis, with Akkermansia muciniphila or butyrate offering potential
   therapeutic avenues for counteracting CMC-induced AP exacerbation.
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   Video Abstract

Supplementary Information

   The online version contains supplementary material available at
   10.1186/s40168-025-02074-1.

Introduction

   Ultra-processed foods (UPFs), consumption of which characterize up to
   60% of the Western diet, has increased dramatically since the
   mid-twentieth century and is associated with elevated incidence of
   various chronic inflammatory diseases, e.g., metabolic syndrome,
   cardiovascular disease, and cancer [[47]1–[48]3]. One prevalent
   characteristic of UPFs is the inclusion of one or more emulsifiers,
   which are utilized to disperse non-mixable components, ensuring the
   stability of functional ingredients and flavors in food and beverages
   while extending their shelf life. Carboxymethylcellulose (CMC) is one
   of the most common emulsifiers used in the food industry. Despite the
   lack of extensive safety testing, CMC was approved in the 1960s for use
   in foods at concentrations up to 2% (wt/wt) by regulatory agencies,
   including the US Food and Drug Administration and the European
   Commission [[49]4]. One reason for assuming the safety of CMC, as well
   as certain other emulsifiers, is that they are poorly absorbed and
   primarily excreted in feces. However, recent researches demonstrated
   that CMC could influence both human microbiota composition and gene
   expression in vitro, and in mice, which has been found to contribute to
   the development of colitis or metabolic syndrome [[50]4–[51]7]. Most
   publications describe the effects of CMC as “mild” or “subtle,”
   resulting in only “low-grade” and “chronic” inflammation. Nevertheless,
   as of now, no research has investigated the potential involvement of
   emulsifiers, such as CMC, in the development of acute systemic
   inflammation.

   Acute pancreatitis (AP) is the most common cause of hospitalization
   with a gastrointestinal condition, which loads heavy burdens on the
   current healthcare system, and the incidence of AP is increasing
   annually both in the USA and worldwide [[52]8]. Despite the generally
   mild clinical course observed in the majority of cases, a noteworthy
   one-fifth of AP patients develop severe systemic inflammation, leading
   to persistent organ failures and an associated mortality rate of
   approximately 20% [[53]8]. The rising prevalence of AP, occurring
   against the backdrop of relatively stable human genetics, hints at the
   involvement of non-genetic factors—specifically, environmental
   factors—in the pathogenesis of AP. Notably, the surge in AP cases has
   been roughly paralleled by increased consumption of UPFs, raising the
   possibility that certain components, such as emulsifiers, in these
   foods may contribute to the promotion of AP.

   CMC, among the most prevalent emulsifiers, has been extensively studied
   for its role in mediating the negative impacts of UPFs on human health
   [[54]6, [55]9]. While direct evidence is absent, various lines of
   evidence strongly indicate the potential role of CMC in the
   pathogenesis of AP. Firstly, numerous studies propose a fundamental
   role for gut microbiota in AP development [[56]10, [57]11], whereas CMC
   predominantly exerts detrimental impacts through inducing gut dysbiosis
   [[58]5, [59]7]. Secondly, CMC exposure induces alterations in the fecal
   metabolome, such as short-chain fatty acids (SCFAs) and bile acids
   [[60]5], both of which were involved in AP pathgenesis [[61]10,
   [62]12]. Gaining insights into the promotive effects of CMC on AP will
   not only provide novel preventive strategies in AP treatment but will
   also fill the knowledge gap regarding whether CMC can promote acute
   systemic inflammation, offering additional evidence for potential
   adjustments in our policy on CMC.

   As deleterious effects are expected, clinical trials of CMC
   intervention are not ethical, we employed a caerulein-induced AP mouse
   model to evaluate the negative impacts of CMC on AP. Fecal microbiota
   transplantation (FMT) to recipient mice successfully transferred the
   detrimental effects of CMC, indicating that such effects were mediated
   by gut dysbiosis. Notably, an abundance of Akkermansia muciniphila
   showed the most significant correlation with various parameters of AP
   severity. Reduced fecal Akkermansia muciniphila was mechanistically
   linked to SCFA reduction, gut barrier dysfunction, increased LPS
   leakage into the bloodstream, classical monocytes frequency elevation
   in blood, and ultimately, the worsening of AP.

Results

CMC exposure exacerbated caerulein-induced AP

   To study the effect of CMC on AP, C57BL/6 mice were subjected to either
   pure water (PW) or CMC solution (1%) for 4 weeks, followed by
   intraperitoneal injection with caerulein (CAE) or normal saline (NS)
   (Fig. [63]1a). Mice in CMC + CAE group exhibited increased
   pancreas/body weight ratio, higher histologic score, raised serum
   amylase and lipase, as compared to mice in PW + CAE group
   (Fig. [64]1b–f). Additionally, mice in CMC + CAE group displayed higher
   serum proinflammatory cytokines IL-6 and TNF-α (Fig. [65]1g, h). These
   data collectively demonstrated that AP was significantly exacerbated
   after CMC exposure.

Fig. 1.

   [66]Fig. 1
   [67]Open in a new tab

   CMC exacerbated caerulein-induced AP. a Experimental scheme, mice drink
   pure water (PW) or CMC solution (1%) for the first 28 days, and on the
   28th day, after fasting for 8 h, the mice were given intraperitoneal
   injections of either normal saline (NS) or caerulein (CAE),
   respectively. b Pancreas-to-body weight ratio. c Representative images
   of pancreatic H&E staining. d Histologic score. e Serum amylase. f
   Serum lipase. g Serum IL-6. h Serum TNF-α. n = 8. *p < 0.05, **p < 0.01
   and ***p < 0.001****p < 0.0001. CMC, carboxymethylcellulose; AP, acute
   pancreatitis

CMC altered gut microbial composition in mice with AP

   To explore potential changes in gut microbiota resulting from CMC
   exposure, we conducted full-length 16S rRNA amplicon sequencing of
   fecal samples. Notably, alpha diversity significantly decreased in the
   PW + CAE, CMC + NS, and CMC + CAE groups compared to the PW + NS group
   (Fig. [68]2a). We employed principal coordinates analysis (PCoA) to
   evaluate beta diversity, revealing distinct clustering among the four
   groups (Fig. [69]2b). Further examination revealed alterations of gut
   microbiota at various taxonomic levels. Specifically, at the phylum
   level, the CMC + CAE group exhibited a significant increase in the
   relative abundance of Proteobacteria, Campilobactre, and Bacteroidota,
   along with a marked decrease in Verrucomicrobiota and Deferribacterota
   compared to the PW + CAE group (Fig. [70]2c); at the genus level, the
   CMC + CAE group showed higher relative abundance of several bacteria,
   including Escherichia − Shigella, Bacteroides, and
   Clostridium_sensu_stricto_1, while Akkermansia, Muribaculaceae, and
   Lactobacillus were notably reduced compared to the PW + CAE group
   (Fig. [71]2d,e).

Fig. 2.

   [72]Fig. 2
   [73]Open in a new tab

   CMC altered gut microbiota in mice with AP. a Alpha diversity (based on
   Chao1). b PCoA of beta diversity using unweighted unifrac distance.
   Relative abundance of taxa at the phylum (c), and genus (d) levels. e
   The Sankey chart presents the family and genus level pattern of change
   in gut microbiota between the PW + CAE and CMC + CAE groups. f
   Cladograms generated by LEfSe indicating differences in the bacterial
   taxa between PW + CAE and CMC + CAE group. g LDA score for the
   bacterial taxa differentially abundant between PW + CAE and CMC + CAE
   groups (LDA > 4.0). h Boxplot of difference analysis at species level
   (Top 10). i Relative abundance of those potentially pathogenic
   bacteria. n = 8. *p < 0.05, **p < 0.01 and ***p < 0.001****p < 0.0001.
   CMC, carboxymethylcellulose; AP, acute pancreatitis; PW, pure water;
   CAE, caerulein; PCoA, principal coordinate analysis; LDA, linear
   discriminant analysis; LEfSe, linear discriminant analysis effect size

   To identify the specific bacteria associated with CMC-induced AP
   exacerbation, we conducted an in-depth analysis of bacterial
   differences between the PW + CAE group and the CMC + CAE group. Our
   analysis, including species differences and LEfSe analysis, revealed
   significantly higher relative abundances of Escherichia coli,
   Clostridium perfringens, and Bacteroides vulgatus in the CMC + CAE
   group, whereas Akkermansia muciniphila, Lactobacillus unclassified, and
   Lachnospiraceae bacterium were markedly reduced (Fig. [74]2f–h).
   Additionally, we employed BugBase, a bioinformatics tool for predicting
   community-wide phenotypes, to assess phenotypic differences among the
   four groups. Notably, the relative abundance of potentially pathogenic
   bacteria significantly increased in the CMC + CAE group compared to the
   PW + CAE group (Fig. [75]2i). Collectively, these findings indicate
   that CMC induced alterations in the gut microbiota of mice with AP,
   leading to an increase in potentially pathogenic bacterial abundance.

CMC exacerbated AP in a gut microbiota-dependent manner

   To investigate if alterations of gut microbiota contribute to CMC’s
   negative impacts on AP, we conducted FMT from PW or CMC-exposed mice
   into two different sets of mice: antibiotic-treated
   specific-pathogen-free (SPF) mice (Additional file 1: Fig. S[76]1a) and
   germ-free (GF) mice (Fig. [77]3a).

Fig. 3.

   [78]Fig. 3
   [79]Open in a new tab

   FMT from mice exposed to CMC exacerbated AP in GF mice. a Schematic
   diagram of the experimental design using germ-free (GF) mice. Mice in
   the GF-FMT-Ctrl group received FMT from control mice on the first 7
   days, while mice in the GF-FMT-CMC group received FMT from mice exposed
   to CMC, and on the 7th day, after fasting for 8 h, mice in two groups
   were given intraperitoneal injections of caerulein (CAE) to induce AP.
   b Principal coordinates analysis (PcoA) plot assessing beta diversity.
   Relative abundance distribution of bacteria in phylum (c) and genus (d)
   level. e The cladogram representing the significantly different
   microbial features between GF-FMT-Ctrl and GF-FMT-CMC groups. f Linear
   discriminant analysis effect size (LEfSe) analysis showing bacterial
   taxa that were significantly different in abundance between GF-FMT-Ctrl
   and GF-FMT-CMC groups. g Relative abundance of potentially pathogenic
   bacteria predicted based on the BugBase database. h Representative
   images of pancreatic H&E staining. i Pancreas-to-body weight ratio. j
   Histologic score. k Serum amylase. l Serum lipase. m Serum IL-6. n
   Serum TNF-α. n = 8. *p < 0.05, **p < 0.01 and
   ***p < 0.001****p < 0.0001. GF mice, germ-free mice; FMT, fecal
   microbiota transplantation

   The gut microbiota of recipient mice was profiled after FMT.
   Beta-diversity analysis showed distinct microbial communities between
   FMT-Ctrl and FMT-CMC groups (Additional file 1: Fig. S[80]1b), as well
   as between GF-FMT-Ctrl and GF-FMT-CMC groups (Fig. [81]3b). Consistent
   with microbiota alteration between PW + CAE and CMC + CAE groups, the
   FMT-CMC/GF-FMT-CMC groups exhibited a significant increase in the
   relative abundance of Bacteroidota and Desulfobacterota, while
   Verrucomicrobiota levels markedly decreased at the phylum level; at the
   genus level, the FMT-CMC/GF-FMT-CMC groups had higher relative
   abundance of various bacteria, including
   Desulfovibrionaceae_unclassified, Alloprevotella, and Bacteroides,
   while Akkermansia and Lactobacillus were noticeably reduced
   (Fig. [82]3c-f, Additional file 1: Fig. S[83]1c–f). Predictions based
   on the BugBase database showed potentially pathogenic bacteria
   abundance increased in the FMT-CMC/GF-FMT-CMC groups compared to the
   FMT-Ctrl/GF-FMT-Ctrl groups (Fig. [84]3g, Additional file 1: Fig.
   S[85]1g).

   In both experimental models, mice receiving FMT (FMT-CMC/GF-FMT-CMC)
   from CMC-exposed donors exhibited more severe pancreatic tissue damage,
   as evidenced by higher pancreas-to-body weight ratio, elevated
   histologic scores (Fig. [86]3h–j, Additional file 1: Fig. S[87]1h–j),
   increased serum levels of amylase, lipase, IL-6, and TNF-α
   (Fig. [88]3k–n, Additional file 1: Fig. S[89]1k–n), compared to those
   receiving FMT from control donors. FMT from CMC-exposed mice
   transferred adverse effects to both SPF and GF recipient mice, which
   demonstrated the crucial role of gut dysbiosis in CMC-induced AP
   exacerbation.

scRNA-seq identified classical monocytes as top altered immune cells in
FMT-CMC group

   Mounting evidence suggests that gut microbiota can influence distant
   organs by regulating immunity [[90]13, [91]14]. To further elucidate
   mechanisms behind CMC-induced AP exacerbation, we employed single-cell
   RNA sequencing (scRNA-seq) to study the cellular heterogeneity of
   peripheral blood mononuclear cells (PBMCs) in the FMT-Ctrl and FMT-CMC
   groups.

   Fifteen cell clusters, derived from six major clusters, including
   monocytes, DCs, T cells, basophils, NK cells, and B cells, were
   identified (Fig. [92]4a, Additional file 1: Fig. S[93]2a–d). Cell
   number for each cluster and sample was displayed to confirm the
   clustering’s accuracy (Fig. [94]4b). Top markers for each cluster were
   shown in a heatmap (Fig. [95]4c). Interestingly, we observed a
   significantly higher frequency of monocytes in the FMT-CMC group
   compared to the FMT-Ctrl group (p = 0.017), with no differences among
   the other major clusters (Fig. [96]4d). Specifically, classical
   monocytes, which are known for their pro-inflammatory roles in AP
   [[97]15], exhibited significant differences between the two groups
   (Fig. [98]4e).

Fig. 4.

   [99]Fig. 4
   [100]Open in a new tab

   scRNA-seq identified classical monocytes as top altered immune cells in
   mice received FMT from mice exposed to CMC. a Uniform Manifold
   Approximation and Projection plot: 15 cell types identified by
   scRNA-seq. b Cell number and composition of different cell types in
   FMT-Ctrl and FMT-CMC group. c The top DEGs of each major cell type. The
   red color in the heatmap means highly expressed genes. d The cell
   composition differences between the FMT-Ctrl and FMT-CMC groups for
   each major cell cluster-monocytes, Dcs, T cells, basophils, Nk cells,
   and B cells. Ns, not significant. e The cell composition differences
   between FMT-Ctrl and FMT-CMC groups for each monocyte subgroup. ns, not
   significant. f Gene weight rank for FMT-CMC VS FMT-Ctrl samples in
   scRNA-seq data by GSEA analysis. Different colors of curves represent
   the significant pathways. g GSVA result heatmap for pathways activity
   in FMT-Ctrl and FMT-CMC group by progeny. Scaled, red for highly
   enriched, blue for lowly enriched. h Trajectory feature plots for
   classical monocytes in pseudotime analysis. The S1–S5 five directions
   have different cell compositions. The bright color represents the late
   stage. i DEGs in the early and late stages during pseudotime. Scaled,
   red for highly expressed, blue for lowly expressed. The horizon axis
   represents the stage from early to late. j Bubble plot for cell–cell
   interaction level between Mono_classical cells and other cells, only
   shows the significant interactions in CellphoneDB (p < 0.05). Scaled,
   red for highly interacted, blue for lowly interacted. n = 4

   Gene set variation analysis (GSVA) and transcriptional regulon analysis
   indicated that classical/intermediate monocytes displayed more
   pro-inflammatory features than Non-classical monocytes (Additional file
   1: Fig. S3a, c). GSEA analysis for classical monocytes reported
   upregulation of cell communication (NES = 1.82), cytokine production
   (NES = 1.89), and immune system process pathways (NES = 2.06) in the
   FMT-CMC group (Additional file 1: Fig. S3b). Pro-inflammatory pathways
   were significantly upregulated in FMT-CMC group cells compared to
   FMT-Ctrl group cells, including cellular response to interleukin-1
   (NES = 2.08), inflammatory response (NES = 2.07), and myeloid leukocyte
   migration pathways (NES = 1.93) (Fig. [101]4f). PROGENy analysis also
   revealed enrichment of JAK-STAT, NFκB, and TNFα pathways in FMT-CMC
   group cells (Fig. [102]4g).

   Next, we used Monocle 2 to infer the developmental trajectory of
   classical monocytes, dividing them into five states (S1-S5) along
   pseudotime (Fig. [103]4h). Classical monocytes from the FMT-CMC group
   were predominantly enriched in S4 and S5, representing relatively late
   pseudotime states (Fig. [104]4h). Transcriptional analysis revealed two
   distinct gene sets associated with inflammatory roles in classical
   monocytes (Fig. [105]4i). Cell–cell communication analysis highlighted
   significant factors between classical monocytes and other cells
   (Fig. [106]4j). These findings suggest that FMT from CMC-exposed mice
   increases classical monocytes in recipient mice peripheral blood,
   potentially contributing to CMC-induced AP exacerbation.

Analysis of upstream regulators revealed that LPS-stimulated C/EBPδ drives
monocytes towards classical phenotype

   Regulon activity was calculated to assess upstream regulons driving the
   heterogeneity of monocytes. We found that CCAAT/enhancer-binding
   protein delta (C/EBPδ) was the most specific regulon associated with
   classical monocytes based on RNA profiles (Fig. [107]5a). Meanwhile,
   the expression level of C/EBPδ in classical monocytes surpasses that in
   all other cell types within PBMCs (Fig. [108]5b). UMAP plot provides
   additional support that the activity of C/EBPδ was highly specific to
   classical monocytes (Additional file 1: Fig. S4a). To determine the
   effect of C/EBPδ expression on monocytes polarization, we transfected
   RAW264.7 cell with pC/EBPδ or siC/EBPδ for 48 h. Transfection efficacy
   was validated by quantitative reverse-transcription PCR (qRT-PCR)
   (Fig. [109]5c). We found that overexpression of C/EBPδ in RAW264.7 cell
   resulted in significant increase of levels of classical monocytes
   markers, e.g., S100a8, S100a9, Lcn2, Cxcl2, and Ifitm1, whereas
   knockdown of C/EBPδ did the opposite, demonstrating that C/EBPδ plays a
   critical role in polarization of monocytes towards pro-inflammatory
   (classical) phenotype (Fig. [110]5c).

Fig. 5.

   [111]Fig. 5
   [112]Open in a new tab

   C/EBPδ induced by LPS is a key transcriptional factor for classical
   monocyte activation. a Regulons activity ranks in classical monocytes.
   b Violin plots indicating the C/EBPδ expression levels in different
   cell types of PBMCs. c The relative expression of classical monocyte
   markers in control and C/EBPδ-overexpressed RAW264.7 cells, analyzed by
   qRT-PCR. The mRNA expression levels of each gene were normalized to
   fold over β-actin (housekeeping gene) (n = 3). d The diagram of
   monocytes C/EBPδ knockdown mice preparation. AAV-DIO-shRNA (C/EBPδ) or
   AAV-DIO-shRNA (NC) was injected into Cx3cr1-iCre Cas9-KI mice’ tail
   vein. e Monocyte-specific C/EBPδ knockdown mouse experiment. On the
   first day, Cx3cr1-iCre Cas9-KI mice were injected intravenously with
   AAV-DIO-shRNA (C/EBPδ) or AAV-DIO-shRNA (NC) based on their group
   assignment, and then they were provided with pure water or CMC solution
   (1%) to drink, depending on their group, for a 28-day intervention
   period. On day 28, AP was induced in all four groups using caerulein. f
   Representative images of pancreatic H&E staining. g Histologic score. h
   Flow cytometry (FCM) analysis showed proportions of classical monocytes
   in PBMC of mice (n = 3). i Gene weight rank for FMT-CMC monocytes VS
   FMT-Ctrl monocytes in scRNA-seq data by GSEA analysis. Different colors
   of curves represent the significant pathways. j Serum LBP of FMT-Ctrl
   and FMT-CMC groups (n = 8). k Serum LBP of PW + NS, PW + CAE, CMC + NS,
   and CMC + CAE groups (n = 8). l The relative expression of classical
   monocyte markers in RAW264.7 cells treated with blank, LPS (10 ng/ml),
   LPS (10ng/ml) + sh-C/EBPδ, analyzed by qRT-PCR. The mRNA expression
   levels of each gene were normalized to fold over β-actin (housekeeping
   gene) (n = 3). m Eritoran rescue experiment design (n = 8). In Ctrl and
   Ctrl + Eritoran groups, mice took pure water for 28 days, and on day
   28, the Ctrl group received an intraperitoneal injection of NS, while
   the Ctrl + Eritoran group received an intraperitoneal injection of
   Eritoran. In CMC and CMC + Eritoran groups, mice took CMC solution (1%)
   for 28 days. On day 28, the CMC group received an intraperitoneal
   injection of NS, while the CMC + Eritoran group received an
   intraperitoneal injection of Eritoran. One hour after the injection of
   NS or Eritoran, AP was induced in all four groups using caerulein. n
   Representative images of pancreatic H&E staining. o Histologic score. p
   Flow cytometry (FCM) analysis showed proportions of classical monocytes
   in PBMC of mice (n = 4). *p < 0.05, **p < 0.01 and ***p < 0.001
   ****p < 0.0001. AP, acute pancreatitis; LBP, lipopolysaccharide-binding
   protein; PBMCs, peripheral blood mononuclear cells

   To investigate the role of monocytes C/EBPδ in the process of CMC
   worsening AP. We conducted a monocyte-specific C/EBPδ knockdown mouse
   experiment. On the first day, Cx3cr1-iCre Cas9-KI mice were injected
   intravenously with AAV-DIO-shRNA (C/EBPδ) or AAV-DIO-shRNA (NC) based
   on their group assignment, and then they were provided with pure water
   or CMC solution (1%) to drink, depending on their group, for a 28-day
   intervention period. On day 28, AP was induced in all four groups using
   caerulein (Fig. [113]5d, e). qPCR results demonstrate that we
   successfully achieved a specific knockdown of C/EBPδ in mouse monocytes
   (Additional file 1: Fig. S4b). Compared to the AAV-DIO-shRNA(NC) + CMC
   group, mice in the AAV-DIO-shRNA(C/EBPδ) + CMC group showed significant
   alleviation of AP, characterized by lower histological scores
   (Fig. [114]5f,g), pancreatic/body weight (Additional file 1: Fig. S4c),
   serum amylase, serum lipase, serum IL-6, and serum TNF-α levels
   (Additional file 1: Fig. S4d–g). Additionally, the proportion of
   classical monocytes in the PBMCs of the AAV-DIO-shRNA(C/EBPδ) + CMC
   group was reduced compared to the AAV-DIO-shRNA(NC) + CMC group
   (Fig. [115]5h, Additional file 1: Fig. S4h), as illustrated in the
   gating strategy shown in Additional file 1: Fig. S4i. Our results
   demonstrate that monocyte-specific C/EBPδ knockdown can reverse the
   increase in the proportion of classical monocytes caused by CMC,
   alleviate the exacerbation of AP induced by CMC.

   We further investigated the potential factor contributing to
   upregulation of C/EBPδ. GSEA analysis showed that the inflammatory
   response lps up (NES = 1.79) pathway was among the most significantly
   enriched pathways in the FMT-CMC group (Fig. [116]5i). Serum LBP
   (lipopolysaccharide-binding protein) levels were measured as an
   indirect indicator of LPS levels. Quantification of serum LBP further
   confirmed its elevated profile in both the CMC exposure group and
   recipient mice that received feces from CMC-exposed mice.
   (Fig. [117]5j, k; Additional file 1: Fig. S5a), aligning with its
   established role as a C/EBPδ activator in previous studies [[118]16].
   In vitro analysis demonstrated that LPS stimulation induced a
   noticeable increase in the expression levels of C/EBPδ and classical
   monocytes markers in RAW264.7 cells, conversely, knockdown of C/EBPδ
   attenuated these effects (Fig. [119]5l). These findings collectively
   demonstrate the causal relationship between LPS and C/EBPδ activation,
   as well as classical monocytes polarization.

   Given that elevated serum LPS is usually associated with increased
   intestinal permeability, we further investigated the impact of CMC on
   gut barrier function in AP mice. Levels of tight junction proteins in
   the gut epithelium, including Zonula occludens-1 (ZO-1) and claudin-1,
   were significantly decreased following direct or indirect (via FMT)
   exposure to CMC (Additional file 1: Fig. S6a–l). These findings
   indicate that CMC exposure led to the impairment of the gut barrier,
   resulting in increased serum LPS levels in AP mice.

   We further conducted a rescue experiment utilizing eritoran, a
   competitive antagonist of LPS (Fig. [120]5m), to assess the
   contribution of elevated serum LPS to CMC-induced AP aggravation.
   Intraperitoneal injection of eritoran in CMC-exposed AP mice resulted
   in a reduction of histologic score (Fig. [121]5n, o) and
   pancreas-to-body weight ratio (Additional file 1: Fig. S5b), along with
   decreased serum levels of amylase, lipase, IL-6, and TNF-α (Additional
   file 1: Fig. S5c–f). Consistently, the frequency of classical monocytes
   in PBMCs decreased in the CMC + Eritoran group compared to the CMC
   group (Fig. [122]5p, Additional file 1: Fig. S5g). Collectively, these
   data indicate that C/EBPδ-driven classical monocyte activation, induced
   by impaired gut barrier and subsequent LPS leakage, plays a crucial
   role in mediating the promotive effects of CMC on AP.

Butyrate supplementation ameliorates AP exacerbation induced by CMC

   Since SCFAs protect gut barrier integrity through nourishing intestinal
   epithelial cells [[123]17], we quantified SCFA levels in the feces of
   mice. Compared to PW + CAE, CMC + CAE showed decreased propionate,
   butyrate, and total SCFA concentrations (Fig. [124]6a–d). Furthermore,
   total SCFAs, acetate, propionate, and butyrate, in the feces of he
   FMT-CMC/GF-FMT-CMC group were significantly lower compared to
   FMT-Ctrl/GF-FMT-Ctrl group (Additional file 1: Fig. S7a–h). To identify
   the specific subtype of SCFAs responsible for CMC-induced AP
   exacerbation and gut barrier impairment, we did correlation analysis
   and found that butyrate exhibited the most potent correlation with AP
   severity parameters (Fig. [125]6e). Then we conducted a rescue
   experiment to validate butyrate’s potential effects in mitigating AP
   severity (Fig. [126]6f). Fecal butyrate deletion due to CMC exposure
   were reversed by butyrate gavage (Fig. [127]6g).

Fig. 6.

   [128]Fig. 6
   [129]Open in a new tab

   Butyrate relieved AP aggravated by CMC. Fecal total SCFAs (a), acetate
   (b), propionate (c), and butyrate (d) concentration (n = 8). e
   Correlation analysis between feces SCFAs and AP phenotype and gut
   barrier function identifies the contributing feces metabolite. f
   Butyrate rescue experiment design (n = 8). In the Ctrl group, mice took
   pure water for 28 days, on days 14–28 supplementing water gavage. In
   the CMC and CMC + Butyrate groups, mice took CMC solution (1%) for 28
   days, on days 14–28, supplementing water gavage for the CMC group and
   butyrate solution gavage for the CMC + Butyrate group. g Fecal butyrate
   concentration. h Pancreas-to-body weight ratio. i histologic score. j
   Representative images of pancreatic H&E staining. The gut barrier
   function of mice was evaluated and compared by western blot (k) and
   immunofluorescence (l) of ZO-1 and claudin-1 protein. m Serum LBP
   level. n Flow cytometry (FCM) analysis showed proportions of classical
   monocytes in PBMCs of mice (n = 4). *p < 0.05, **p < 0.01 and
   ***p < 0.001 ****p < 0.0001. LBP, lipopolysaccharide-binding protein;
   PBMCs, peripheral blood mononuclear cells

   Butyrate supplementation significantly ameliorates CMC’s detrimental
   effects on AP, with reduced levels of a list of AP severity parameters,
   e.g., pancreas-to-body weight ratio, histologic score (Fig. [130]6h-j),
   serum amylase, lipase, IL-6, TNF-α (Additional file 1: Fig. S7i–l).
   Moreover, gut barrier function was partially restored, with increased
   levels of ZO-1 and claudin-1 (Fig. [131]6k, l; Additional file 1: Fig.
   S7m, n), and decreased serum LBP level (Fig. [132]6m). Classical
   monocyte frequency in PBMCs was also decreased (Fig. [133]6n;
   Additional file 1: Fig. S7o). These results suggest that butyrate
   depletion plays a role in the adverse effects of CMC on AP, and
   supplementation with butyrate mitigates these effects.

Akkermansia muciniphila supplementation ameliorates AP exacerbation induced
by CMC

   We employed correlation matrices to further identify specific gut
   bacteria that relate to the detrimental effects of CMC. Among the five
   significantly altered bacteria strains, including Akkermansia
   muciniphila, Escherichia coli, Clostridium perfringens, Bacteroides
   vulgatus, Alistipes unclassified, and Akkermansia muciniphila exhibited
   the strongest correlation with AP severity. A diminished abundance of
   Akkermansia muciniphila was associated with elevated serum LPS, IL-6,
   TNF-α, pancreas-to-body weight ratio, and pancreatic histologic score,
   as well as lowered gut barrier makers (ZO-1, claudin-1) and fecal SCFAs
   levels (Fig. [134]7a), which are in line with Akkermansia muciniphila’s
   established role as a crucial beneficial probiotic that fortifies the
   gut barrier [[135]18].

Fig. 7.

   [136]Fig. 7
   [137]Open in a new tab

   Akkermansia muciniphila alleviating AP aggravated by CMC. a Correlation
   analysis between gut bacteria abundance and disease phenotype
   identifies the contributing gut bacterium on pancreatitis phenotype and
   gut barrier function. b Akkermansia muciniphila rescue experiment
   design (n = 8). In the Ctrl group, mice took pure water for 28 days, on
   days 14–28 supplementing PBS gavage. In the CMC and CMC + AKK groups,
   mice took CMC solution (1%) for 28 days, on days 14–28, supplementing
   PBS gavage for the CMC group and Akkermansia muciniphila gavage for the
   CMC + AKK group. c Akkermansia muciniphila abundance by qRT-PCR. d
   Pancreas-to-body weight ratio. e Histologic score. f Representative
   images of pancreatic H&E staining. Gut barrier function of mice was
   evaluated and compared by western blot (g) and immunofluorescence (h)
   of ZO-1 and claudin-1 protein. i Serum LBP level. j Flow cytometry
   (FCM) analysis showed proportions of classical monocytes in PBMCs of
   mice (n = 4). k Schematic protocal. l Boxplot of difference analysis at
   the species level (Top 5). m The correlation between Akkermansia
   muciniphila abundance and the BISAP score of AP patients was analyzed
   using Spearman’s correlation. o The correlation between Akkermansia
   muciniphila abundance and CRP level of AP patients was analyzed using
   Spearman’s correlation. *p < 0.05, **p < 0.01 and ***p < 0.001
   ****p < 0.0001. LBP, lipopolysaccharide-binding protein; PBMCs,
   peripheral blood mononuclear cells. AKK, Akkermansia muciniphila

   We further conducted a rescue experiment to validate Akkermansia
   muciniphila’s potential effects in mitigating AP severity
   (Fig. [138]7b). Administration of Akkermansia muciniphila through
   gavage significantly increased its relative abundance in CMC + AKK
   group (Fig. [139]7c). This led to a reduction in pancreas-to-body
   weight ratio and histologic score (Fig. [140]7d–f), decreased serum
   amylase, lipase, IL-6, and TNF-α (Additional file 1: Fig. S8a–d),
   restored gut barrier function (Fig. [141]7g–i, Additional file 1: Fig.
   S8e, f) and elevated fecal SCFAs (Additional file 1: Fig. S8g–j), as
   compared with CMC group. Classical monocyte levels in PBMCs
   concordantly decreased in the CMC + AKK group compared to the CMC group
   (Fig. [142]7j; Additional file 1: Fig. S8k). In summary, Akkermansia
   muciniphila supplementation alleviated AP, reinforced gut barrier, and
   elevated fecal SCFAs in the context of CMC exposure.

   We further performed a correlation analysis between Akkermansia
   muciniphila abundance and AP severity in humans. The gut microbiota of
   54 AP patients were assessed using full-length 16S rRNA sequencing
   (Fig. [143]7k). Compared with mild AP (MAP) group, moderately severe or
   severe (MSAP/SAP) group showed lower alpha diversity (Additional file
   1: Fig. S9a). PCoA was used to assess the β-diversity based on
   bray–curtis (ANOSIM R = 0.0444, p = 0.088) distances between the
   MSAP/SAP and MAP groups (Additional file 1: Fig. S9b). At the phylum
   level, the relative abundance of Proteobacteria was significantly
   increased, while Verrucomicrobiota abundance was drastically decreased
   in MSAP/SAP group compared with that in MAP group (Additional file 1:
   Fig. S9c); at the genus level, the relative abundance of
   Escherichia − Shigella was higher, whereas Akkermansia, Muribaculaceae,
   and Ruminococcaceae were noticeably decreased in MSAP/SAP group
   compared with that in MAP group (Additional file 1: Fig. S9d, e).
   Differential analysis of species level suggests that Escherichia coli
   abundance was increased while Akkermansia muciniphila was decreased in
   MSAP/SAP group compared with that in MAP group (Fig. [144]7l).
   Moreover, Akkermansia muciniphila abundance showed a negative
   correlation with the bedside index for severity in AP (BISAP) score
   [[145]8] (Fig. [146]7m) and C-reactive protein (CRP) (Fig. [147]7o).
   Based on the presence or absence of Systemic Inflammatory Response
   Syndrome (SIRS) in AP, the cases were divided into SIRS and non-SIRS
   groups, compared to the non-SIRS group, the abundance of AKK was
   significantly reduced in the SIRS group (Additional file 1: Fig. S9f).
   These findings suggest that diminished gut Akkermansia muciniphila may
   be a potential indicator for severe AP (Fig. [148]8).

Fig. 8.

   [149]Fig. 8
   [150]Open in a new tab

   Mechanism diagram

Discussion

   Though various studies showed that environmental factors, e.g., the
   Western diet, contribute a lot to the annual increase of AP incidence,
   no previous research reported the role of those ubiquitous food
   additives in AP pathogenesis. The current study demonstrated for the
   first time that one common food additive, CMC, worsens AP, which is
   accompanied with gut dysbiosis. Through FMT from CMC-exposed mice to
   SPF or GF mice, an exaggerated AP phenotype was transferred, suggesting
   that altered gut microbiota mediates CMC’s adverse effects on AP.
   Single-cell sequencing identified classical monocytes as potential key
   effector cells in mediating AP promotion by CMC. CMC exposure led to
   reduced fecal SCFAs, especially butyrate, contributing to increased
   intestinal permeability and exacerbating AP by allowing LPS into the
   bloodstream. Mechanistically, elevated serum LPS upregulated C/EBPδ in
   monocytes, promoting the activation of classical monocytes, thereby
   exacerbating AP. This gut microbial shift is featured with increased
   pathogenic bacteria and reduced probiotics, with Akkermansia
   muciniphila showing the strongest correlation with AP severity.
   Supplementation with Akkermansia muciniphila or butyrate mitigated
   CMC-induced AP exacerbation.

   Numerous studies highlighted CMC’s detrimental impacts on human health
   by disrupting gut microbiota [[151]4, [152]5], which induces low-grade
   inflammation and promotes the development of chronic diseases. However,
   no research to date has explored the potential impact of CMC on acute
   inflammatory diseases. AP is a pancreatic disorder triggered by damage
   to acinar cells, leading to both local and systemic inflammations. The
   degree of systemic inflammation in AP varies, with potential
   complications and life-threatening conditions in certain cases.
   Multiple evidence supports the potential pathogenic role for gut
   dysbiosis in AP. For example, gut microbiota differs both between AP
   patients and healthy volunteers [[153]19] and among AP patients with
   different severity grades [[154]20]. Depleting the gut microbiota using
   antibiotics alleviates AP in mice [[155]21]. All these findings drive
   us to explore if CMC could regulate AP through modulating gut
   microbiota. Our data showed that CMC exposure significantly altered gut
   microbiota in the setting of AP, reducing α-diversity and increasing
   potential pathogenic bacteria. Concurrently, certain probiotics,
   including Akkermansia muciniphila and Lactobacillus unclassified,
   decreased. FMT from CMC-exposed mice to GF and antibiotics-treated SPF
   mice successfully transferred the AP-promotive phenotype, indicating
   that gut microbiota mediates the adverse effects of CMC on AP.

   We further explored the molecular mechanism underlying CMC’s negative
   effects on AP. Since exaggerated AP is characterized with enforced
   systemic inflammation, we hypothesized if certain immune cell types in
   circulation mediate the detrimental impacts of CMC. We conducted
   scRNA-seq analysis on PBMCs from FMT-Ctrl and FMT-CMC groups. Among the
   six major cell clusters (monocytes, DCs, T cells, basophils, NK cells,
   and B cells), only the frequency of monocytes was significantly
   increased in the FMT-CMC group. Further analysis revealed a marked
   increase in the classical subtype (Ly6C +), a well-known
   inflammation-initiator monocyte type, with the ability to differentiate
   into macrophages within tissues [[156]22]. This aligns with their
   pro-inflammatory role during the AP process [[157]15], indicating their
   involvement in classical monocytes’ promotive effects on AP. Regulons
   activity analysis revealed that C/EBPδ stands out as the most specific
   regulon associated with classical monocytes. Enforced expression of
   C/EBPδ in RAW264.7 cells significantly upregulated those marker genes
   for classical monocytes, while knockdown of C/EBPδ did the opposite,
   emphasizing its critical role in classical monocyte activation.
   Further, we conducted an experiment involving monocyte-specific
   knockdown of C/EBPδ in mice. This targeted knockdown was found to
   reverse the CMC-induced increase in the proportion of classical
   monocytes and alleviate the exacerbation of acute pancreatitis (AP)
   caused by CMC. In summary, these studies demonstrate the critical role
   of C/EBPδ in the CMC-aggravated AP process.

   We further employed GSEA analysis to identify the upstream factor
   contributing to C/EBPδ upregulation. In the FMT-CMC group, the
   signaling pathway regarding LPS, a known stimulator on C/EBPδ
   [[158]23], was significantly enriched, aligning with its elevated
   profile in serum, as compared to the FMT-Ctrl group. Intraperitoneal
   administration of eritoran, an LPS antagonist [[159]24], successfully
   alleviated CMC-induced AP exacerbation, with classical monocyte
   frequency significantly reduced, which highlights the pivotal role of
   LPS in mediating the detrimental effects of CMC on AP. Gut barrier
   function analysis showed significantly increased intestinal
   permeability, as evidenced by diminished expressions of ZO-1 and
   Claudin-1, which contributed to elevated serum LPS levels.
   Mechanistically, CMC exposure increases gut permeability, facilitates
   translocation of LPS into bloodstream, thereby upregulates C/EBPδ,
   which activates classical monocytes and finally results in AP
   exaggeration.

   UPFs, including those food additives, are endemic in our modern
   societies, making it difficult for many people to shift towards less
   processed diets with reduced food additives within the current food
   systems in a short time. We investigated if certain elements can help
   counteract the deleterious impacts of CMC against AP. We conducted a
   correlation analysis to pinpoint specific microbes and metabolites
   associated with the CMC’s promotion of AP. Five bacteria (Akkermansia
   muciniphila, Escherichia coli, Clostridium perfringens, Bacteroides
   vulgatus, Alistipes unclassified) and three major SCFAs (acetate,
   propionate, butyrate) with most significantly altered profiles were
   selected as the candidates. Notably, both Akkermansia muciniphila and
   butyrate exhibited strong correlations with various AP severity and gut
   barrier function parameters, indicating their potential involvement in
   CMC-related AP exacerbation. Supplementation with Akkermansia
   muciniphila or butyrate alleviated CMC-induced AP aggravation.
   Interestingly, Akkermansia muciniphila supplementation notably restored
   SCFA levels, especially propionate and butyrate, consistent with its
   role as an SCFA producer, revealing that diminished Akkermansia
   muciniphila contributes to the reduced butyrate levels after CMC
   exposure. Further, we detected the gut microbiota in patients with
   pancreatitis and found a negative correlation between the abundance of
   Akkermansia muciniphila and the severity of pancreatitis. We
   acknowledge that our data have limitations. Our AP patient cohort
   primarily consisted of individuals with biliary pancreatitis, this
   predominance may introduce bias, as gut microbiome and barrier function
   can vary with different AP etiologies. Thus, we must be cautious in
   extending our results to the broader spectrum of AP etiologies.

   There remains controversy regarding whether probiotics prophylaxis can
   help reduce AP severity. From a positive perspective, evidence from
   preclinical studies suggests that probiotics could stabilize the
   intestinal barrier and minimize bacterial translocation, thus
   preventing infection in AP [[160]25]. Clinical trials have documented
   the benefits of probiotics in some critically ill patients [[161]26].
   However, the results of the PROPATRIA trial showed negative outcomes
   [[162]27]. In patients with predicted severe AP, probiotic prophylaxis
   did not reduce the risk of infectious complications and was associated
   with an increased risk of mortality [[163]27]. As of now, probiotics
   use is rarely recommended in clinical practice guidelines [[164]26].
   Significant heterogeneity among different trials is attributed to the
   type, dose, and timing of probiotic treatment [[165]28]. In this study,
   we identified that the administration of Akkermansia muciniphila can
   help alleviate AP, providing novel targets for the development of
   interventional strategies to mitigate the adverse effects of CMC on AP.

Conclusions

   In conclusion, our research demonstrated for the first time that CMC
   exposure aggravates AP in mouse model, which is dependent on altered
   gut microbiota. Depletion of probiotics like Akkermansia muciniphila
   results in reduced SCFAs, compromised gut barrier, and LPS leakage,
   leading to classical monocyte activation and exacerbation of AP.
   Although our study has limitations, such as lacking of clinical
   correlation data between CMC exposure and AP, ignorance of other
   potential probiotics besides Akkermansia muciniphila with protective
   effects against CMC, absence of substantial therapeutic effectiveness
   of Akkermansia muciniphila and butyrate on AP in clinic, our research
   still has certain significance: given the extensive use of CMC in
   processed foods, our research unveiled a significant risk factor
   contributing to the increasing incidence of AP in recent years;
   moreover, our study has direct translational implications for those
   patients who exposed to CMC in daily diet, suggesting that
   supplementing with Akkermansia muciniphila or butyrate could
   potentially prevent AP attacks or alleviate their severity.

Methods

Animals

   All experimental procedures and mouse care were approved by the
   Shanghai Changhai Hospital Ethics Committee. Six-week-old male C57BL/6
   mice were purchased from GemPharmatech Co., Ltd. (Jiangsu, China) and
   kept under specific pathogen-free conditions on a 12-h light–dark cycle
   at a temperature of 20 °C and 40–60% humidity, with free access to
   water. Mice were exposed to carboxymethylcellulose (CMC) (Sigma, Cat.
   No. C4888) diluted in the drinking water (1.0% w/v). The same water was
   used for the pure water-treated (PW) group. These solutions were
   changed every 3 days. At the beginning of the experiment, 32 mice were
   randomly divided into four groups: (1) PW + NS; (2) PW + CAE, acute
   pancreatitis (AP) induction at day 28; (3) CMC + NS; (4) CMC + CAE,
   n = 8 for each group, AP induction at day 28. All mice were kept in
   autoclaved cages with three to five mice per cage; cages were cleaned
   once a week.

Caerulein (CAE)-induced AP

   Mice were fasted for 8 h and were then injected with normal
   saline/caerulein (intraperitoneally, 100 μg/kg body weight, 8 times at
   1-h intervals) (ApexBio Technology, Cat. No. B8465, TX, USA) depending
   on grouping. Mice were sacrificed 24 h after the first injection.
   Pancreatic tissue was isolated and weighed. The blood, feces, and colon
   were collected for further measurements.

Histopathology

   For histological analysis, pancreatic tissue was fixed in 10%
   neutral-buffered formalin, paraffin-embedded, and processed. A 5-µm
   section was stained with H&E and semiquantitatively scored according to
   Schmidt’s criteria (Table S[166]1) by two board-certified veterinary
   pathologists in a blinded manner. The final score is calculated by
   averaging these two values.

Serum amylase and lipase quantifications

   The blood was centrifuged (2000 rpm) for 10 min after standing at room
   temperature for 0.5 h. Supernatants were collected to obtain serum.
   Serum was used to detect amylase (Nanjing Jiancheng Bioengineering
   Institute, Cat. No. C016-1–1) and lipase (Nanjing Jiancheng
   Bioengineering Institute, Cat. No. A054-2–1) levels according to the
   manufacturer’s instructions.

Quantification of cytokine levels

   The serum TNF-α (Anogen, Cat. No. MEC1003) and IL-6 (Anogen, Cat. No.
   MEC1012) levels were measured by ELISA kits according to the
   manufacturer’s instructions.

Full-length 16S ribosomal DNA (rDNA) sequencing

   Fecal genomic DNA from different samples was extracted using the CTAB
   according to the manufacturer’s instructions. The full-length 16S rRNA
   gene was amplified using primers 27F: 5′-AGRGTTTGATYNTGGCTCAG-3′ and
   1492R: 5′-TASGGHTACCTTGTTASGACTT-3′, which were tagged with specific
   barcode per sample. PCR amplification was performed in a total volume
   of 20 μL reaction mixture containing 4 μL of 5 × FastPfu buffer, 2 μL
   of 2.5 mM dNTPs, 0.8 μL of each primer (5 μM), 0.4 μL of FastPfu
   polymerase, and 10 ng of template DNA, and PCR-grade water to adjust
   the volume. The PCR conditions to amplify the FL prokaryotic 16S rRNA
   gene consisted of an initial denaturation at 95 ℃ for 2 min; 25 cycles
   of denaturation at 95 ℃ for 30 s, annealing at 55 ℃ for 30 s, and
   extension at 72 ℃ for 1 min; and then final extension at 72 ℃ for 5
   min.

   The PCR products were confirmed with 2% agarose gel electrophoresis,
   and purified using the AxyPrep DNA Gel Extraction Kit (Axygen
   Biosciences, USA) according to the manufacturer’s instructions. After
   quantification by QuantiFluor TM-ST (Promega, USA), the amplicon pools
   were prepared for library construction. SMRTbell libraries were
   prepared using the Pacific Biosciences SMRTbellTM Template Prep kit 1.0
   (PacBio, USA) and sequenced on PacBio RS II (LC-Bio Technology Co.,
   Ltd., Hangzhou, China).

   Circular consensus sequence (CCS) reads were generated from raw
   subreads by SMRT Link (v6.0) with the following parameters:
   minPasses = 5; minPredictedAccuracy = 0.9. Then lima (v1.7.1) was used
   to distinguish CCS reads from different samples, and cutadapt (v1.9)
   was applied to identify primers. The CCS reads between 1200 to 1650 bp
   remained after the length filtration. After dereplication and filtering
   chimeric sequences using DADA2, we obtained a feature table and feature
   sequence. Alpha diversity and beta diversity were calculated by
   normalizing them to the same sequences randomly. Alpha diversity was
   applied in analyzing the complexity of species diversity for a sample
   through five indices, including Chao1, Observed species, Goods
   coverage, Shannon, Simpson, and all these indices were calculated with
   QIIME2. Beta diversity was calculated by QIIME2. The ASVs were
   annotated by aligned feature sequences with the SILVA database (release
   138). Other diagrams were implemented using the R packages.

Fecal microbiota transplantation (FMT)

   In the SPF mice FMT experiment, all mice took pure water as drinking
   water. Mice were given a four antibiotics cocktail (neomycin sulfate
   200 mg/kg, metronidazole 200 mg/kg, ampicillin 200 mg/kg, and
   vancomycin 100 mg/kg) via oral gavage for 7 consecutive days before FMT
   to pre-deplete the endogenous gut microbiota. All the antibiotics used
   here were purchased from Sangon Biotech (Cat. Nos. A610366, A600633,
   A610028, and A600983; Shanghai, China). FMT was performed once daily
   for two weeks after a 1-d recovery of antibiotics cocktail. For the FMT
   experiments, we collected 200–300 mg fresh fecal samples from control
   mice and mice exposed to CMC between 15:00 and 17:00. Fresh fecal
   samples were homogenized in PBS, filtered through a 100-μm cell
   strainer, and centrifuged at 7000 g for 5 min; recipient mice were
   administered 200 μl of the supernatant via oral gavage. Recipient mice
   in the FMT-Ctrl/FMT-CMC group received gut microbiota from control mice
   or mice exposed to CMC for 2 weeks respectively.

Germ-free (GF) mice FMT

   Germ-free C57BL/6 mice (6–8 weeks) were bred and maintained in special
   plastic isolators (GemParmatech, Nanjing, China), and experiments were
   approved by GemParmatech IACUC (GPTAP20221024-4). All mice were housed
   under a strict 12-h light cycle (lights on at 08:00). Animals were
   supplied with a 50-kGy irradiated sterile pelleted normal chow diet
   (Xietong Shengwu, Nanjing, China) and autoclaved tap water ab libitum.
   Bedding was replaced in all experiments every 7 days. All germ-free
   mice were routinely screened for bacteria, viral, and fungus
   contamination.

   FMT donor mice were housed in the animal laboratory of Changhai
   Hospital. The donor mice were either exposed or not exposed to CMC.
   Donor feces were collected and prepared into fecal microbial
   suspensions, which were then shipped to the laboratory where germ-free
   mice were kept. Subsequently, FMT was performed via gavage.

10X Single-cell RNA sequencing: samples and analysis

   The whole blood (approximately 0.8 mL) was obtained from each mouse in
   these two groups (n = 4 per group). PBMCs were isolated from whole
   blood by Ficoll gradient separation [[167]29]. Cell suspensions were
   then performed for scRNA-seq. The library was established by 10X
   genomics recommendation for 3′ tag Single Cell Gene Expression
   (10 × Genomics, Pleasanton, CA). The libraries were sequenced by
   Illumina HiSeq6000 (Illumina, San Diego, CA). The 10X Single-Cell
   Software Cell Ranger was used to process raw data, which aligned the
   sequenced reads under the mm10 mouse reference genome and quantified
   single-cell expression level, also removed low-quality reads. A total
   of 65,960 cells were included in the downstream analysis after quality
   filtration. Of those cells, 29,951 cells were FMT-Ctrl-derived and
   36,009 cells were FMT-CMC-derived.

   Downstream analyses were performed by R (4.2.0) and the “Seurat”
   package (4.1.1) [[168]30]. Cells with < 200 or > 5000 genes or with
   more than 10% mitochondrial genes were considered low-quality and
   filtered [[169]31]. Doublets were identified and removed by the package
   “DoubletFinder” (2.0.1). After quality control, ounts were normalized
   by “NormalizeData.” We used the “Harmony” package (1.0) to minimize
   batch differences. The top 30 principal components and the top 2000
   variable genes were applied. We used the “FindClusters” function of
   Seurat (resolution = 6) for cell clustering and visualized them by
   “RunUMAP” function in 2D uniform manifold approximation and projection
   (UMAP).

   Markers of each cell cluster were identified through “FindAllMarker”
   function. The differentially expressed genes (DEGs) were calculated by
   “FindMarkers” function. The adjusted p value < 0.01 was used as the
   cutoff threshold value. The DEGs were then processed by clusterProfiler
   package (3.18.0) for Gene set enrichment analysis (GSEA) pathways
   enrichment analysis. Gene set variation analysis (GSVA) was used
   depending on the C2, C5, KEGG, hallmark, and WP gene set from the
   molecular signature database, as the instructions of the GSVA package
   (1.38.0) for each cell with default parameters. The “progeny” package
   (1.18.0) was applied to analyze several classical pro-inflammatory
   pathway activities for single cells [[170]32].

   To investigate the regulon network, we used pySCENIC, a Python-based
   algorithm in Jupyter Notebook software (1.0.0), to reconstruct
   transcription states and regulatory networks from scRNA-SEQ data. We
   identified differences in area under the curve (AUC) between cells or
   between modules calculated by SCENIC (1.2.2) of cell clusters.
   Regulation of p value (adv. P val) > 0.01 was excluded for further
   study.

   In order to explore the transcriptional alternations of FMT-Ctrl and
   FMT-CMC, we utilized Monocle (2.18.0) for single-cell dramatic
   pseudotime trajectories [[171]33]. The RNA counts were included in
   “Monocle2” for analysis. “Differential GeneTest” function was used to
   build a potential developmental trajectory.

   CellphoneDB (based on Python 3.7) [[172]34] and cellchat (1.6.1)
   [[173]35] were calculation tools for cell–cell communication analysis.
   The cell clusters were investigated to establish cell interaction
   networks. The ligand-receptor pairs with a p value < 0.05 were
   considered to be the significant interaction.

Cell culture

   The mouse macrophage line RAW264.7 was purchased from Procell Life
   Science&Technology (Wuhan, China) and cultured with Dulbecco’s modified
   Eagle medium (DMEM) (10,569,044, Gibco, Carlsbad, CA) containing 10%
   fetal bovine serum (10,099,141, Gibco) and 100 U/mL penicillin and 100
   μg/mL streptomycin at 37 °C with 5% CO[2].

Cell transfection

   The RAW264.7 macrophages (4 × 10^5cells/well) were seeded in a 6-well
   plate. Upon cell confluence reaching 70–80%, cells were grouped and
   transfected with C/EBPδ overexpression plasmid (oe-C/EBPδ) or plasmids
   carrying short hairpin RNA targeting C/EBPδ(sh-C/EBPδ). All plasmids
   and siRNAs (20 uM/uL) were transfected using the Advanced DNA RNA
   Transfection Reagent™ (ZETA LIFE, USA) according to the manufacturer’s
   protocol. Briefly, plasmid or siRNA was directly mixed with
   transfection reagent according to 1:1 relationship, then mixed by
   blowing into a pipette 10–15 times. Following incubation at room
   temperature for 10–15 min, the complex was added to the cell culture
   plates, mixed gently, and incubated in the CO[2] incubator for 24 h.
   Sequences and plasmids used were all provided by RiboBio (Shanghai,
   China).

Monocyte C/EBPδ knockdown mice experiment

   Cx3cr1-iCre Cas9-KI mice (Strain NO. T006768) were purchased from
   GemPharmatech (Nanjing, China). Monocyte C/EBPδ knockdown mice were
   produced by tail vein injection of
   pAAV-CMV-DIO-EGFP-miR30shRNA(Cebpd)-WPRE into Cx3cr1-iCre Cas9-KI mice.
   After the injection of AAV, mice were provided with pure water or CMC
   solution (1%) based on their group assignment for a 28-day intervention
   period. Following this, acute pancreatitis was induced using caerulein.

Quantitative reverse-transcription PCR (qRT-PCR)

   The total RNA of tissue and cells was extracted using Trizol reagent
   (Invitrogen, #15,596,026) according to the manufacturer’s instructions.
   RNA concentration and quality were measured by Nanodrop One
   Spectrophotometers (Thermo Fisher Scientific). RNA was
   reverse-transcribed to cDNA using HiScript III RT SuperMix for
   quantitative RT-PCR (+ gDNA wiper) (Vazyme Biotech, R223-01), and
   qRT-PCR was performed on Lightcycler 480 II system (Roche) using ChamQ
   Universal SYBR quantitative RT-PCR master mix (Vazyme Biotech,
   Q711-02). The expression level was normalized to the housekeeping Actb
   gene, and data were analyzed using the 2-ΔΔCT method. Primers used in
   qRT-PCR are shown in Table S[174]2.

Quantification of LBP (lipopolysaccharide-binding protein) levels

   The serum LBP level was measured with an ELISA kit (Elabscience,
   E-EL-M3090) according to the manufacturer’s instructions.

Immunofluorescence assay

   Colon sections were deparaffinized, antigen retrieved, blocked, and
   incubated with antibodies zo-1 (Proteintech, 21,773–1-AP) and claudin-1
   (Servicebio, [175]GB112543). After incubation with DAPI, the slides
   were scanned under a panoramic midi digital slice scanner (3DHISTECN,
   Budapest, Hungary).

Western blot

   The total protein of colonic tissue was extracted by RIPA lysis buffer
   (Beyotime, P0013C) containing proteinase inhibitors cocktail (Epizyme,
   GRF101). Protein concentrations were determined by the BCA Protein
   Assay Kit (Beyotime, P0012). Tissue lysates were electrophoresed on
   SurePAGE 4–12% Bis–Tris gels (GeneScript, M00654), then transferred to
   Immobilon-P PVDF transfer membrane (Millipore, IPVH00010). Skim milk
   (BioFroxx, 1172GR500) was used for blocking non-specific binding sites.
   The following antibodies were used in western blot: beta actin
   monoclonal antibody (1:100,000, proteintech, 66,009–1-Ig) as an
   internal reference, and ZO-1 polyclonal antibody (1 µg/mL, Invitrogen,
   61–7300), claudin 1 polyclonal antibody (1:1000, proteintech,
   13,050–1-AP) as primary antibodies. The HRP-linked anti-rabbit IgG
   (1:10,000, WESTANG BIO-TECH, C0151) and HRP-linked anti-mouse IgG
   (1:10,000, WESTANG BIO-TECH, C0152) were chosen according to the
   primary antibodies. Signals were visualized using the Immobilon ECL
   Western Substrate (Millipore, WBKLS0100), and images were acquired
   using the Amersham Imager 600 system (GE Life Science).

Eritoran rescue experiment

   Mice were divided into four groups: Ctrl, Ctrl + Eritoran, CMC, and
   CMC + Eritoran. In Ctrl and Ctrl + Eritoran groups, mice took pure
   water for 28 days, and on day 28, the Ctrl group received an
   intraperitoneal injection of NS (100 μl), while the Ctrl + Eritoran
   group received an intraperitoneal injection of Eritoran (2.33 mg/ml,
   100 μl) (MCE, 185,955–34-4). In CMC and CMC + Eritoran groups, mice
   took CMC solution (1%) for 28 days. On day 28, the CMC group received
   an intraperitoneal injection of NS (100 μl), while the CMC + Eritoran
   group received an intraperitoneal injection of Eritoran (2.33 mg/ml,
   100 μl) (MCE, 185,955–34-4). One hour after the injection of NS or
   Eritoran, AP was induced in all four groups using caerulein.

Flow cytometry and antibodies

   PBMCs were isolated from whole blood by Ficoll gradient separation.
   Cell viability and cell surface marker staining were performed at 4 °C
   in the dark at first. When cell staining was completed, cells were
   acquired and detected with the CytoFLEX Flow Cytometer (Beckman
   Coulter). FlowJo v.10 (TreeStar) was used for data analysis. The
   antibodies used in the flow cytometry analysis were all sourced from
   Invitrogen: anti-CD45 (BioLegend, 103,107); anti-CD11b (BioLegend,
   101,212); anti-Ly-6C (BioLegend, 128,007); and anti-Ly-6G (BioLegend,
   127,628).

Short-chain fatty acid (SCFA) quantification analysis

   Feces (20 mg per mouse) (excluding intestinal tissue) were homogenated
   for 1 min with 500 μL of water and 100 mg of glass beads and then
   centrifuged at 4 ℃ for 10 min at 12,000 rpm. Two hundred microliter
   supernatant was extracted with 100 μL of 15% phosphoric acid and 20 μL
   of 375 μg/mL 4-methylvaleric acid solution as IS and 280 μL ether.
   Subsequently, the samples were centrifuged at 4 ℃ for 10 min at 12,000
   rpm after vortexing for 1 min and the supernatant was transferred into
   the vial prior to GC–MS analysis. The extracted samples were detected
   using trace 1310 gas chromatograph (Thermo Fisher Scientific, USA) and
   ISQ 7000 (Thermo Fisher Scientific, USA). SCFA standards were mixtures
   of acetate, propionate, butyrate, isobutyrate, valerate, isovalerate,
   and hexanoate. All the standards were purchased from Sigma (Darmstadt,
   Germany).

Butyrate rescue experiment

   In the Ctrl group, mice were provided with pure water for a duration of
   28 days, whereas mice in the CMC/CMC + Butyrate group were administered
   a 1% CMC solution over the same period. From day 14 to day 28, mice in
   the CMC + Butyrate group underwent daily gavage with butyrate (200
   mg/kg/d, Sigma-Aldrich, 303,410), while mice in the Ctrl/CMC group
   received daily gavage with pure water. AP was induced on day 28.

Akkermansia muciniphila administration and quantification

   Akkermansia muciniphila was purchased from ATCC (ATCC Number: BAA-835)
   and cultured in 0.5% (wt/vol) mucin-supplemented brain heart infusion
   (BHI) (Difco, MI, USA) medium anaerobically at 37 °C. After 48 h of
   incubation, the cultures were centrifuged at 7000 g for 15 min, washed
   twice in sterile saline, and resuspended at a bacterial concentration
   of 1.5 × 10^10 CFU/mL by measuring absorbance at 630 nm for further
   intragastric administration. Mice in the CMC + AKK group were orally
   gavaged with 3 × 10^9 CFU Akkermansia muciniphila suspended in 0.2 mL
   of PBS per day, while mice in the Ctrl and CMC groups were treated with
   an equivalent dose of PBS. The treatments were administered for 14
   days.

   Akkermansia muciniphila quantification was detected by qRT-PCR, and the
   relative abundance of Akkermansia muciniphila was calculated using the
   previously published method [[176]36]. The primers used in
   quantification: Total Bacteria (Bacteria Universal)
   F-ACTCCTACGGGAGGCAGCAG, R-ATTACCGCGGCTGCTGG; Akkermansia muciniphila
   F-CAGCACGTGAAGGTGGGGAC, R-CCTTGCGGTTGGCTTCAGAT.

Patient and public involvement statement

   Patients were included from July 15, 2023, to August 15, 2023. A total
   of 54 newly diagnosed AP patients, including 23 mild AP (MAP), 12
   moderate severe AP, and 19 severe AP, were enrolled for full-length 16s
   rRNA sequencing. Severity was defined as MAP (mild), MSAP (moderate
   severe), or SAP (severe) according to the revised Atlanta criteria.
   Information regarding age and sex is recorded in Table S3 for each
   individual patient. The exclusion criteria of this study were as
   follows: antibiotic/probiotics usage within 3 months and chronic
   gastrointestinal diseases. All patients provided written informed
   consent. The study was approved by the Shanghai Changhai Hospital
   Ethics Committee (CHEC2023-159).

Statistical analysis

   Numeric data were expressed as mean ± S.E.M, data with normal
   distribution were compared by Student’s t-test, while data with
   abnormal distribution were compared by Wilcoxon rank-sum test. p < 0.05
   was considered statistically significant. All statistical analyses were
   performed on GraphPad Prism v9.3.1 and R v4.0.2 software.

Supplementary Information

   [177]40168_2025_2074_MOESM1_ESM.docx^ (46.8MB, docx)

   Additional file 1: Supplementary figure.
   [178]40168_2025_2074_MOESM2_ESM.docx^ (17.9KB, docx)

   Additional file 2: Supplementary tables.

Acknowledgements