Skip to main content

Altered microbiome of serum exosomes in patients with acute and chronic cholecystitis



This study aimed to investigate the differences in the microbiota composition of serum exosomes from patients with acute and chronic cholecystitis.


Exosomes were isolated from the serum of cholecystitis patients through centrifugation and identified and characterized using transmission electron microscopy and nano-flow cytometry. Microbiota analysis was performed using 16S rRNA sequencing.


Compared to patients with chronic cholecystitis, those with acute cholecystitis exhibited lower richness and diversity. Beta diversity analysis revealed significant differences in the microbiota composition between patients with acute and chronic cholecystitis. The relative abundance of Proteobacteria was significantly higher in exosomes from patients with acute cholecystitis, whereas Actinobacteria, Bacteroidetes, and Firmicutes were significantly more abundant in exosomes from patients with chronic cholecystitis. Furthermore, functional predictions of microbial communities using Tax4Fun analysis revealed significant differences in metabolic pathways such as amino acid metabolism, carbohydrate metabolism, and membrane transport between the two patient groups.


This study confirmed the differences in the microbiota composition within serum exosomes of patients with acute and chronic cholecystitis. Serum exosomes could serve as diagnostic indicators for distinguishing acute and chronic cholecystitis.

Peer Review reports


Cholecystitis, caused by cholecystolithiasis, microbial infection, ischemia, allergic reaction, and chemical damage, is one of the common digestive tract diseases [1]. Based on the duration of the condition, cholecystitis can be classified into acute and chronic types [2]. Acute cholecystitis is often triggered by gallstone obstruction or other lesions causing biliary obstruction, leading to bile stasis and gallbladder inflammation. It is a common cause of acute abdominal pain [3]. According to statistical data, the incidence of acute cholecystitis is approximately 7.45-10.06%, with a higher prevalence among the elderly, reaching 5-10% [4]. Although most cases of acute cholecystitis can be cured through conservative treatment or open surgery, improper management may result in severe complications such as pancreatitis, cirrhosis, liver failure, and even life-threatening situations [5,6,7]. Chronic cholecystitis, on the other hand, is a prevalent chronic gastrointestinal disorder, accounting for 60-80% of all cholecystitis cases. Its main symptoms include periodic or persistent mild to moderate pain [8,9,10]. While the prognosis for chronic cholecystitis is generally favorable, prolonged inflammation and damage may increase the risk of developing gallbladder cancer [11]. Currently, the treatment strategies differ between acute and chronic cholecystitis. Acute cases necessitate timely cholecystectomy or percutaneous cholecystostomy for high-risk patients, coupled with antibiotic therapy. Conversely, chronic cholecystitis can often be treated through elective cholecystectomy [12]. Therefore, it is crucial to diagnose and differentiate between acute and chronic cholecystitis accurately and promptly. This differentiation is vital in avoiding potential complications associated with emergency surgery or intervention, as well as preventing disease progression into complicated gallbladder conditions.

The human microbiome refers to the diverse array of bacteria, viruses, fungi, protozoa, and archaea present on and inside the human body [13]. Scientific evidence indicates that only 1% of human DNA originates from the human genome, while the remaining 99% is derived from the microbiome [14]. Although most microbes may not directly harm the human body, they exert a significant influence on human health and are closely associated with the onset and progression of various diseases [15]. Within the human gallbladder and bile, a diverse microbial community exists. Several studies have identified different bacterial communities from bile and gallbladder walls of cholecystitis patients through microbial isolation and culture methods [16]. Research has demonstrated that dysbiosis in the microbiome plays a crucial role in the development of cholecystitis [17]. However, the differences in microbial composition between patients with acute and chronic cholecystitis remain unclear. Therefore, investigating the microbial composition of patients with acute and chronic cholecystitis is essential for the diagnosis of these conditions.

Exosomes are small vesicles with a diameter of approximately 30–150 nm, released by cells and found in various bodily fluids [18]. Exosomes function by encapsulating diverse genetic materials, including DNA fragments, and RNA, as well as functional proteins such as enzymes and receptors. They transport these materials to target cells, regulating gene expression, cell signaling, and other biological processes within the target cells [19]. During cholecystitis, exosomes release inflammation mediators and regulatory factors, leading to sustained or exacerbated inflammatory responses [20]. Additionally, the genetic materials within exosomes may participate in regulating gene expression and signaling pathways associated with cholecystitis, further influencing the development and progression of the condition [21]. Studies have indicated that certain bacteria can directly enter exosomes, inducing exosome release and affecting the quality and composition of exosomes [22]. Exosomes derived from infected cells or those carrying microorganisms such as bacteria and viruses play a significant role in host immune responses and disease progression [23]. Hence, investigating the microbial composition within exosomes from patients with acute and chronic cholecystitis is essential for gaining a deeper understanding of the underlying mechanisms and diagnostic and therapeutic approaches for these conditions. However, there is no reported evidence regarding whether the differences in microbial composition carried by exosomes in patients with acute and chronic cholecystitis impact the development of the condition.

In this study, we utilized 16 S rRNA sequencing technology to analyze the microbial composition within serum exosomes of patients with acute and chronic cholecystitis. Simultaneously, we identified potential metabolic pathways within the detected microbial communities. Our research delineated the microbial distinctions in serum exosomes between acute and chronic cholecystitis, providing novel insights into the pathogenesis and diagnosis of these conditions.

Materials and methods

Sample collection

A total of 39 serum samples were collected from 17 patients with acute cholecystitis and 22 patients with chronic cholecystitis. Patients clinically diagnosed with acute cholecystitis were categorized as the Acute group (n = 17), while those diagnosed with chronic cholecystitis were classified as the Chronic group (n = 22). No participants had taken probiotics, antibiotics, or related medications within 60 days before the study. All participants were free from severe organic diseases such as heart, lung, kidney, and other infectious diseases. Written informed consent was obtained from all participants. The research protocol was approved by the Ethics Committee of Xiamen Chang Gung Hospital (NO. CMRPG1G0161).

Isolation of exosomes

The patients’ serum specimens were subjected to a 300 g low-speed centrifugation for 10 min to remove cellular components. Subsequently, a 2000 g low-speed centrifugation for 10 min was performed to eliminate dead cells, followed by a 10,000 g centrifugation for 70 min to eliminate cell debris. Next, a 120,000 g high-speed centrifugation for 60 min was conducted to obtain pelletized extracellular vesicles. The vesicles were resuspended in an appropriate volume of PBS to eliminate contaminating proteins and subjected to another 120,000 g centrifugation for 60 min. The precipitate was collected and resuspended in PBS, and the samples were stored at -80 °C.

Characterization of exosomes

The morphology of exosomes was examined using transmission electron microscopy (TEM) with negative staining. The isolated exosomes were stained with 2% uranyl acetate for 1 min in a total volume of 10 mL, placed onto grids, and observed using a TEM operating at 80 kV (JEM-1400Plus, JEOL Ltd, Tokyo, Japan). Additionally, following previously reported experimental methods from our laboratory [24, 25], exosomes concentration and size in serum were analyzed using nano-flow cytometry (nFCM) with a nanoanalyzer, following the manufacturer’s instructions.

DNA extraction from exosomes

The exosomes were lysed using an appropriate amount of pancreatic protease to release internal DNA. Following the manufacturer’s instructions precisely, total DNA was extracted from the lysate of extracellular vesicles using a DNA extraction kit (Rengenbio, China). The concentration of DNA was determined using the NanoDrop assay, and the integrity and purity of DNA were evaluated through 1% agarose gel electrophoresis.

16S amplification and deep sequencing

To characterize the microbiota within extracellular vesicles, we employed a novel method for amplification and sequencing of 16S rRNA. This method involves amplification of 68% of the bacterial 16S rRNA gene using short amplicons [26]. Previous studies have provided comprehensive details regarding this methodology [27]. The amplification of five regions of the 16S rRNA gene was performed using 100 ng of DNA, a set of 10 multiplex primers, 0.2 mM dNTPs sourced from Larova GmbH, and 0.02 U/µL of Phusion Hot Start II DNA Polymerase (Thermo Scientific). After combining 40–50 amplicons into sub-libraries, each sub-library underwent purification utilizing the Qiaquick PCR purification kit (QIAGEN, Germany) as per the manufacturer’s guidelines. Subsequently, multiple sub-libraries were pooled to create the final library. Subsequently, further purification from primer dimers was conducted using Agencourt AMPure XP (Beckman Coulter) at a volumetric ratio of 1:0.85 (Library: beads), followed by supplementation of the library with 15% PhiX (8 pM). Finally, paired-end sequencing was performed on the Illumina NovaSeq 6000 platform, generating paired-end reads with a length of 150 bp.

Microbiome analyses

After sequencing data were obtained, demultiplexing was performed for each sample based on barcode recognition. Subsequently, the cutadapt plugin was utilized to remove additional primers from the paired-end reads. The sequences were then subjected to quality filtering, denoising, merging, and chimera removal using the DADA2 plugin [28]. To explore the taxonomic composition of each sample, operational taxonomic units (OTUs) were clustered at 97% sequence similarity. Venn diagrams were generated to compare the shared OTUs between the two sample groups. Taxonomic annotation was carried out using the Greengenes_12_8 database with QIIME2 software, providing relative abundance information for each sample [29]. For analyzing the microbial communities in exosomes between the two sample groups, α-diversity and β-diversity analyses were conducted. Alpha-diversity analysis reflects the complexity and diversity of species within each sample and was computed using QIIME2 software, including observed species, ACE, Simpson, and Shannon indices. Weighted and unweighted UniFrac distances were calculated using QIIME 2 software. Principal coordinates analysis (PCoA) was visualized using ggplot2 and ade packages in R, and arithmetic distances were interpreted using an unweighted pair-group method with arithmetic mean (UPGMA) hierarchical clustering based on the average linkage algorithm for clustering analysis.

Furthermore, to analyze the compositional changes of microbial communities within exosomes between the two sample groups, Metastat software was employed for relative abundance analysis of microbial communities at the phylum, class, order, family, and genus levels. Linear discriminant analysis effect size (LEfSe) was utilized to assess the effect size of significantly different taxa at different taxonomic levels. Tax4Fun package in R software was used for functional prediction of microbial communities within extracellular vesicles based on the 16S SILVA database [30]. 16S rRNA gene sequences were extracted from the KEGG prokaryotic genome database [31], and aligned to the SILVA SSU Ref NR database using the BLASTN algorithm to create a related matrix [32]. The annotated functional information of the KEGG prokaryotic genome was mapped to the SILVA database using UproC and PAUDA methods for functional annotation. Finally, OTUs were clustered from the sequenced samples using SILVA database sequences as reference sequences to obtain functional annotation information.

Statistical analysis

All experimental data were statistically analyzed using GraphPad Prism version 8.0 (GraphPad Software, San Diego, CA, USA) and presented as mean ± standard deviation (SD). Differences between the two groups in extracellular vesicle size and α-diversity analysis were evaluated using unpaired t-tests, while the significance of other differences in distributions was assessed using Kruskal-Wallis tests. A P-value < 0.05 was considered statistically significant.


Clinical characteristics of participants

The demographic information of all participants is presented in Table 1. The age range of the participants varied from 26 to 71 years old. In the Acute group, the average age of patients was (51 ± 11) years, with a white blood cell (WBC) count of (8.83 ± 3.43)×109/L and C-reactive protein (CRP) levels of (24.02 ± 41.45) mg/L. In the Chronic group, the average age of patients was (45 ± 12) years, with a WBC count of (6.65 ± 2.06)×109/L and CPR levels of (1.21 ± 0.88) mg/L.

Table 1 Characteristics of patients with acute and chronic cholecystitis

Phenotypic characterization of exosomes

Exosomes were isolated from both the Acute and Chronic groups and identified and confirmed using TEM. TEM analysis revealed that the exosomes exhibited typical cup-shaped vesicles (Fig. 1A). There were no significant differences in the average diameter and concentration of exosomes between the Acute and Chronic groups (Fig. 1B, C). Purity analysis of exosomes was conducted using nFCM, which showed positive surface markers (CD9 and CD81) compared to the blank IgG control group (Fig. 1D). These results demonstrate the successful isolation of exosomes in this study. Overall, these findings indicate the effective separation of exosomes.

Fig. 1
figure 1

The characterization of exosomes from the Acute group and Chronic group. A Observation of electron micrographs of exosomes by transmission electron microscopy (TEM) (Bar = 100 nm). B Measurement of exosomes diameter using nanoflow cytometry (nFCM). C Measurement of exosomes concentration using nFCM. D Detection of surface markers CD9 and CD81 expression on exosomes using nFCM, with blank IgG used as a negative control.

Difference of microbiota between acute group and chronic group

The rarefaction curve analysis revealed a sharp increase followed by a plateau for each sample, indicating that the sequencing depth was sufficient to reflect the microbial diversity in exosomes (Fig. 2A). The sequences were clustered and classified into operational taxonomic units (OTUs) with 97% similarity, resulting in a total of 1164 OTUs across both groups (Supplementary Table S1). The Venn analysis showed 589 OTUs for the Acute group and 961 OTUs for the Chronic group, with 386 OTUs shared between the two groups (Fig. 2B), indicating both similarities and differences in microbial communities within exosomes of patients from these two groups. To further analyze the changes in microbial communities within exosomes of the two groups, this study conducted α-diversity analysis, including the Observed species index representing richness, Shannon and Simpson indices representing diversity, and Abundance-based Coverage Estimator (ACE) evaluating abundance coverage. The α-diversity analysis results demonstrated that, compared to the Chronic group, the Acute group exhibited decreased Observed_species index (P < 0.01) and ACE index (P < 0.01) as well as reduced Shannon index (Fig. 2C–E). Conversely, the Simpson index was higher (Fig. 2F), indicating a higher abundance and diversity of microbial communities in the exosomes of the Chronic group. Furthermore, β-diversity analysis was conducted to estimate the similarity of microbial communities between the two groups. Distances between samples were calculated using Jaccard and Unweighted_UniFrac metrics, and Principal Coordinates Analysis (PCoA) was performed on the distance matrices. Jaccard_PcoA and Unweighted_UniFrac_PcoA analysis results showed significant separation between the two groups (Fig. 3A, B), and both Jaccard and Unweighted_UniFrac distances exhibited significant differences between the two groups (P < 0.001) (Fig. 3C, D). Additionally, Anosim analysis was employed to assess the significance of β-diversity, revealing statistically significant differences in microbial community composition between the two groups (Jaccard_Anosim: 0.202, P = 0.001; Unweighted_UniFrac_Anosim: R = 0.188, P = 0.001). These results indicated significant differences in microbial communities within the exosomes of patients from the two groups.

Fig. 2
figure 2

Alpha diversity analysis of microbial communities in exosomes of patients with acute and chronic cholecystitis. A The rarefaction curve. B Venn diagram showing the distribution of OTUs in the Acute and Chronic groups. C Box plot depicting the number of observed species (Observed_species index). D Abundance-based Coverage Estimator (ACE) used to estimate the number of unobserved species and calculate the estimation of the total species count. E Shannon index reflecting species richness and evenness. F Simpson index measuring species diversity and evenness within the community. **P < 0.01. ns, no significant difference. A: Acute group; B: Chronic group

Fig. 3
figure 3

Beta diversity analysis of microbial communities in exosomes of patients with acute and chronic cholecystitis. A Investigation of β-diversity changes in microbial communities within exosomes using Jaccard_PcoA analysis between the two groups. B Investigation of β-diversity changes in microbial communities within exosomes using Unweighted UniFrac_PcoA analysis between the two groups. C Jaccard distances between samples from the two groups. D Unweighted_UniFrac distances between samples from the two groups. E Anosim analysis of Jaccard dissimilarities. F Anosim analysis of Unweighted_UniFrac dissimilarities. ***P < 0.001

Bacterial composition at different taxonomic levels

To further analyze the differential microbial communities in exosomes of patients with acute and chronic cholecystitis, we assessed the relative abundances of the top 10 taxa at the phylum, class, family, and species levels. At the phylum level, Proteobacteria, Actinobacteria, Bacteroidetes, and Firmicutes were the predominant phyla in both acute and chronic cholecystitis patients (Fig. 4A). Comparatively, in the Acute group, the relative abundance of Actinobacteria (P < 0.01), Bacteroidetes (P < 0.05), and Firmicutes (P < 0.05) significantly decreased, while Proteobacteria significantly increased (P < 0.01) compared to the Chronic group (Supplementary Table S2). At the family level, Moraxellaceae, Burkholderiaceae, Sphingomonadaceae, Rhizobiaceae, Nocardiaceae, and Brevibacteriaceae were the major families identified in both acute and chronic cholecystitis patients (Fig. 4B). Relative abundances of Moraxellaceae (P < 0.01), Burkholderiaceae (P < 0.01), and Sphingomonadaceae significantly increased (P < 0.01) in the Acute group compared to the Chronic group, while Rhizobiaceae (P < 0.01), Nocardiaceae (P < 0.01), and Brevibacteriaceae (P < 0.01) significantly decreased (P < 0.001, Supplementary Table S3). At the genus level, Acinetobacter, Rhodococcus, Brevibacterium, and Burkholderia were the predominant genera in both acute and chronic cholecystitis patients’ exosomes (Fig. 4C). Relative abundances of Brevibacterium (P < 0.001) and Agrobacterium (P < 0.01) significantly decreased in the Acute group compared to the Chronic group (Supplementary Table S4). At the species level, the most abundant microbial species in exosomes of both acute and chronic cholecystitis patients were Acinetobacter calcoaceticus, Rhodococcus globerulus, Burkholderia cepacia, Ralstonia mannitolilytica, Rhizobium radiobacter, and Sphingomonas azotifigens (Fig. 4D). In the Acute group, the relative abundances of Acinetobacter calcoaceticus (P < 0.01), Burkholderia cepacia (P < 0.01), and Ralstonia mannitolilytica (P < 0.001) significantly increased, while Rhodococcus globerulus (P < 0.001) significantly decreased compared to the Chronic group (Supplementary Table S5). These results further indicated significant differences in microbial communities between the Acute and Chronic groups.

Fig. 4
figure 4

Relative abundance of top 10 microbial taxa at different classification levels in exosomes of patients with acute and chronic cholecystitis. A Phylum level. B Family level. C Genus level. D Species level

Analysis of the difference of the microflora in exosomes and prediction of biological function between the two groups

Linear Discriminant Analysis Effect Size (LEfSe) based on logarithmic linear regression analysis (LDA score threshold set at ≥ 4) was employed to reveal key microbial taxa distinguishing the Acute and Chronic groups. Results indicated significant differences between the two groups at various taxonomic levels. At the phylum level, Proteobacteria exhibited a significant increase in relative abundance in the Acute group, while Actinobacteria were significantly elevated in the Chronic group. At the class level, Betaproteobacteria showed a significant increase in the Acute group, whereas Alphaproteobacteria and Coriobacteriia were significantly higher in the Chronic group. At the order level, Burkholderiales, Pseudomonadales, and Sphingomonadales were significantly elevated in the Acute group, whereas Rhizobiales and Actinomycetales were significantly higher in the Chronic group. At the family level, Burkholderiaceae, Moraxellaceae, and Sphingomonadaceae were significantly increased in the Acute group, whereas Nocardiaceae, Brevibacteriaceae, and Rhizobiaceae were significantly higher in the Chronic group. At the genus level, Ralstonia, Acinetobacter, Burkholderia, and Sphingomonas exhibited significant increases in the Acute group, while Rhodococcus, Agrobacterium, and Brevibacterium were significantly elevated in the Chronic group. At the species level, Acinetobacter calcoaceticus, Ralstonia mannitolilytica, Burkholderia cepacia, and Sphingomonas azotifigens showed significant increases in the Acute group, whereas Rhodococcus globerulus exhibited a significant increase in the Chronic group (Fig. 5A, B). All 28 identified microbial taxa demonstrated significant differences between the Acute and Chronic groups (P < 0.05). Furthermore, to predict the functional profiles of microbial communities in plasma exosomes from patients with acute and chronic cholecystitis, Tax4Fun analysis was performed, revealing differences in the enrichment levels of 36 pathways related to amino acid metabolism, carbohydrate metabolism, membrane transport, and signal transduction between the Acute and Chronic groups at the second level of KEGG pathways (Fig. 6).

Fig. 5
figure 5

Differential composition of exosome microbiota in patients with acute and chronic cholecystitis. A Bacteria enriched in exosomes of the Acute group (red) and Chronic group (green). B Bar graph comparing the relative abundances of enriched taxa in exosomes of the Acute group (red) and Chronic group (green).

Fig. 6
figure 6

Tax4Fun functional prediction


Cholecystitis is an inflammatory disease of the digestive system, and exosomes are commonly studied as inflammatory mediators to investigate the pathogenesis of allergic diseases [33, 34]. Currently, most studies have focused on the bile and gut microbiota in healthy individuals and cholecystitis patients, with limited research on the microbial composition within exosomes of patients with acute and chronic cholecystitis. In this study, we analyzed the microbial communities in serum exosomes of patients with acute and chronic cholecystitis. Our findings revealed distinct microbial community characteristics in patients with acute cholecystitis as compared to those with chronic cholecystitis. Specifically, we observed reduced microbial diversity and specific changes in microbial abundance within the serum exosomes of patients with acute cholecystitis. Furthermore, diverse microbial metabolic pathways were also identified between the acute and chronic groups.

This study initially conducted α-diversity and β-diversity analyses on two groups of patients. Alpha-diversity serves as an indicator to measure species diversity within an ecosystem or community, while β-diversity metrics reveal relative differences in microbial communities between patients with acute and chronic cholecystitis [35]. Mora-Guzmán I et al. and Mintz D et al. found that there are differences in microbial profiles in the bile of cholecystitis patients compared to healthy individuals, with lower richness and diversity in patient microbiota [36, 37]. Similarly, in our study, we observed lower bacterial diversity and richness in the Acute group compared to the Chronic group, accompanied by significant alterations in microbial composition between the two groups. These findings indicated distinct microbial community compositions within exosomes in the blood of patients with acute and chronic cholecystitis.

Studies have shown the presence of diverse microbial communities in the biliary tract, where microbial dysbiosis might contribute to the formation of gallstones [17]. Previous research indicated that the Firmicutes, Bacteroidetes, Actinobacteria, and Proteobacteria dominate the bile bacterial composition [38,39,40]. In our study, we observed similar results, particularly noting a significant increase in Proteobacteria in the exosomes of patients with acute cholecystitis. Proteobacteria are highly abundant in the biliary tract [17], constituting approximately 1% of the healthy human gut microbiota [41]. However, in our study, Proteobacteria accounted for over 50% of both acute and chronic cholecystitis exosomes, suggesting an alteration in the microbial composition of cholecystitis patients. An investigation into bile microbiota identified Gram-negative bacteria such as Escherichia coli, Enterobacteriaceae, Pseudomonas aeruginosa, and Klebsiella as predominant pathogenic taxa in cholecystitis patients [42]. Notably, Escherichia coli, Enterobacteriaceae, Pseudomonas aeruginosa, and Klebsiella are members of the Proteobacteria phylum [43]. Among these, Enterobacteriaceae is a major harmful member of the human microbiota [44], associated with various diseases including acute pelvic inflammatory disease, necrotizing enterocolitis, and urinary tract infections [45,46,47]. Liu et al. [48] demonstrated that isolates of Enterobacteriaceae from patients with acute cholecystitis could induce inflammation and morphological changes in animal gallbladders. Additionally, Enterobacteriaceae can impair the intestinal barrier, leading to the translocation of intestinal microbiota to the host’s bloodstream and biliary system [45]. These findings indicate that bacteria from the Enterobacteriaceae family might be the primary pathogenic microorganisms in acute cholecystitis. Sarah J Powers et al. [49] detected Pseudomonas aeruginosa in gallbladder tissue samples from common marmosets (Callithrix jacchus) with cholecystitis. In a study on the microbiota of gallstones and bile, Pseudomonas aeruginosa exhibited the highest glucuronic acid enzyme activity and produced higher concentrations of phospholipase A2, promoting gallstone formation and, consequently, acute cholecystitis [50]. These findings suggest that Pseudomonas aeruginosa might serve as a diagnostic biomarker for acute cholecystitis. In our study, we observed significant differences in the microbial composition within exosome in the blood of patients with acute and chronic cholecystitis. Further analysis revealed significant disparities in the Proteobacteria phylum between the two patient groups. Combined with previous research results, we speculate that varying levels of Proteobacteria could potentially serve as novel biomarkers for diagnosing acute and chronic cholecystitis. Additionally, in our study, we observed a significant decrease in the abundance of Firmicutes, Bacteroidetes, and Actinobacteria phyla in the exosome of patients with acute cholecystitis, indicating potential alterations in these microbial communities in both acute and chronic cholecystitis patients. However, the specific mechanisms underlying these changes require further in-depth investigation.

The microbial community can influence various host metabolic reactions, disease progression, and signaling pathways, thereby regulating growth processes and the onset of chronic diseases [24, 51]. In this study, functional metabolism and physiological pathways affected by acute and chronic cholecystitis were predicted through Tax4Fun analysis. Our findings revealed differential enrichment in 36 pathways between the two patient groups, including amino acid metabolism, carbohydrate metabolism, membrane transport, and signal transduction. Amino acid metabolism encompasses several amino acids. For instance, histidine, as an anti-inflammatory amino acid, can reduce the levels of reactive oxygen species in the body. Studies have shown that histidine expression is decreased in patients with chronic cholecystitis, thereby promoting inflammatory responses in cholecystitis [52]. Moreover, decreased histidine concentrations have been observed in inflammatory chronic kidney diseases [53]. Our study further suggested that the microbial composition in patients with acute and chronic cholecystitis might impact these metabolic pathways.

Currently, the diagnosis of cholecystitis primarily relies on imaging examinations such as ultrasound, CT, and HIDA scans, supplemented by comprehensive evaluation of detailed medical history, thorough clinical examinations, and laboratory test results [54]. These diagnostic modalities have been demonstrated to possess good accuracy in clinical practice. This study revealed significant differences in the microbial communities within serum exosomes of patients with acute and chronic cholecystitis. However, due to the time-consuming nature of microbial analysis and the imperative for immediate surgical intervention once acute cholecystitis is diagnosed, the clinical application of microbial analysis remains supplementary. Gallstones are considered one of the predisposing factors for biliary tract infections. Meanwhile, there have been significant changes in the distribution and resistance of pathogenic microorganisms causing biliary tract infections [55]. In the early stages of acute cholecystitis, bile is typically sterile and becomes infected as a secondary event [56]. Previous studies have indicated that approximately 9-42% of patients undergoing elective laparoscopic cholecystectomy develop bile infections, with the incidence of positive bile cultures in patients with acute cholecystitis rising to 35–65% [56], and to 44% in patients with chronic cholecystitis [55]. For patients with moderate to severe acute cholecystitis, early pathogen eradication based on antibiotics is crucial in limiting systemic sepsis and local inflammation following cholecystectomy [57]. Appropriate initial antibiotic therapy should not be delayed while waiting for culture test results, as this delay may increase the mortality rate of patients with biliary tract infections [43]. Hence, appropriate antibiotic therapy should commence immediately following diagnosis [38]. Gram-negative bacterial strains constitute the major pathogenic microbial population in cholecystitis, with typical gram-negative bacteria (such as Escherichia coli, Pseudomonas aeruginosa, and Klebsiella pneumoniae) belonging to the Proteobacteria family [42]. In this study, we found that Proteobacteria accounted for over 50% of the exosomal microbiota in patients with both acute and chronic cholecystitis. It has been shown that Gram-negative bacterial strains have low susceptibility to cephalosporins, quinolones, and ampicillin [42]. Therefore, alternative antibiotics may need to be considered when selecting antibiotic therapy. These findings suggest that microbial analysis could provide better guidance for treatment [42].

However, this study has certain limitations. Firstly, we only observed changes in the microbial composition of serum exosomes in patients with acute and chronic cholecystitis in this study. However, existing research suggests that the gut microbiota might also be associated with gallbladder diseases. Secondly, the composition of microbiota is influenced by various factors, but this study did not assess the impact of other factors on microbial changes, such as age, gender, diet, and lifestyle. Additionally, once clinically diagnosed with acute cholecystitis, patients require early surgical treatment, while microbial composition analysis may require more time. Therefore, there is a need for further optimization of the workflow for microbiota analysis in the future. Despite these limitations, the findings of this study offer a novel insight into the role of microbial composition in acute and chronic cholecystitis, providing a new approach to the diagnosis of these conditions. However, the conclusions of this study are currently applicable only at the laboratory level. Future research should be conducted on a larger scale to explore the role of microbiota in acute and chronic cholecystitis and to optimize the technology for wider clinical application in the future.


In summary, our study demonstrated significant differences in the composition and diversity of microbiota in serum exosomes between patients with acute and chronic cholecystitis. The notable differences in the abundance of Proteobacteria, Actinobacteria, Bacteroidetes, and Firmicutes hold the promise of serving as novel biomarkers for the clinical diagnosis of acute and chronic cholecystitis. This research contributes to the diagnosis of clinical acute and chronic cholecystitis and provides a theoretical foundation for elucidating the potential mechanisms of microbial metabolism.

Data availability

The sequencing raw data have been deposited into the Sequence Read Archive Database of National Center for Biotechnology Information (NCBI). The BioProject accession number is PRJNA1049960 (


  1. Toro A, Mazzone C, Gaspare Fontana E et al. Cautious aptitude in difficult Acute Cholecystitis to Prevent Catastrophic Complication. J Am Coll Surgeons[J] 2023, 236(2):436.

  2. Yang C, Wangzhe, You F et al. Risk factors and prediction models for acute suppurative cholecystitis. Asian J surgery[J] 2023, 46(4):1608–9.

  3. Stewart CL, Tran TB, Nguyen A et al. Cholecystectomy in patients with hematologic malignancies. Am J surgery[J] 2022, 223(6):1157–61.

  4. Walter K. Acute Cholecystitis. Jama[J]. 2022;327(15):1514.

    Article  PubMed  Google Scholar 

  5. Costanzo ML, D’Andrea V, Lauro A et al. Acute Cholecystitis from Biliary Lithiasis: Diagnosis, Management and Treatment. Antibiotics (Basel, Switzerland)[J]. 2023, 12(3).

  6. Adachi T, Eguchi S, Muto Y. Pathophysiology and pathology of acute cholecystitis: a secondary publication of the Japanese version from 1992. Journal of hepato-biliary-pancreatic sciences[J]. 2022, 29(2):212–6.

  7. Hudson JL, Baron TH. Endoscopic approaches to Cholecystitis. The American journal of gastroenterology[J]. 2023.

  8. Yi W, Perez J, Rosen C et al. Promoting a culture of Safety in Cholecystectomy (COSIC) over a decade at a Philippine public regional hospital after the SAGES International Proctoring Course in Laparoscopic Cholecystectomy Course. Surgical endoscopy[J]. 2023, 37(1):613–6.

  9. Alammari RK, Alhessan AA, Alturki AA, et al. Xanthogranulomatous Cholecystitis: a rare variant of chronic cholecystitis. Cureus[J]. 2022;14(1):e21400.

    Article  PubMed  Google Scholar 

  10. Wang SY, Yeh CN, Jan YY et al. Management of gallstones and Acute Cholecystitis in patients with liver cirrhosis: what should we consider when performing surgery? Gut and liver[J]. 2021, 15(4):517–27.

  11. Jawaid M, El-Sherif T, George A et al. Acute Cholecystitis in a gastric bypass patient complicated by Takotsubo Cardiomyopathy. Case reports in surgery[J]. 2022, 2022:5416092.

  12. Yeo DM, Jung SE. Differentiation of acute cholecystitis from chronic cholecystitis: determination of useful multidetector computed tomography findings. Med (Baltimore)[J]. 2018;97(33):e11851.

    Article  Google Scholar 

  13. Sender R, Fuchs S, Milo R. Revised estimates for the Number of Human and Bacteria Cells in the body. PLoS Biol[J] 2016, 14(8):e1002533.

  14. Yang J, Shin TS, Kim JS et al. A new horizon of precision medicine: combination of the microbiome and extracellular vesicles. Exp Mol Med[J] 2022, 54(4):466–82.

  15. Kandalai S, Li H, Zhang N et al. The human microbiome and cancer: a diagnostic and therapeutic perspective. Cancer Biol Ther[J] 2023, 24(1):2240084.

  16. Grigor’eva IN, Romanova TI. Gallstone Disease and Microbiome. Microorganisms[J] 2020, 8(6).

  17. Limberg J, Egan CE, Mora HA et al. Metagenomic sequencing of the gallbladder microbiome: bacterial diversity does not vary by Surgical Pathology. J Gastrointest Surgery: Official J Soc Surg Aliment Tract[J] 2022, 26(11):2282–91.

  18. Kalluri R, LeBleu VS. The biology, function, and biomedical applications of exosomes. Sci (New York NY)[J] 2020, 367(6478).

  19. Li B, Cao Y, Sun M et al. Expression, regulation, and function of exosome-derived miRNAs in cancer progression and therapy. FASEB journal: official publication of the Federation of American Societies for Experimental Biology[J]. 2021, 35(10):e21916.

  20. Noonin C, Thongboonkerd V. Exosome-inflammasome crosstalk and their roles in inflammatory responses. Theranostics[J] 2021, 11(9):4436–51.

  21. Wang Y, Wang X, Zhang N et al. Extracellular vesicles of Clonorchis sinensis promote IL-6 and TNF-α secretion via the toll-like receptor 9-mediated ERK pathway in biliary epithelial cells. Developmental and comparative immunology[J]. 2023, 139:104555.

  22. Ocansey DKW, Zhang Z, Xu X et al. Mesenchymal stem cell-derived exosome mitigates colitis via the modulation of the gut metagenomics-metabolomics-farnesoid X receptor axis. Biomaterials science[J] 2022, 10(17):4822–36.

  23. Lawson C, Kovacs D, Finding E et al. Extracellular vesicles: Evolutionarily Conserved Mediators of Intercellular Communication. Yale J Biology medicine[J] 2017, 90(3):481–91.

  24. Chiang TY, Yang YR, Zhuo MY et al. Microbiome profiling of nasal extracellular vesicles in patients with allergic rhinitis. World Allergy Organ J[J] 2022, 15(8):100674.

  25. Chang CJ, Zhang J, Tsai YL et al. Compositional features of distinct microbiota base on serum Extracellular Vesicle metagenomics analysis in moderate to severe psoriasis patients. Cells[J] 2021, 10(9).

  26. Parhi L, Alon-Maimon T, Sol A et al. Breast cancer colonization by Fusobacterium nucleatum accelerates tumor growth and metastatic progression. Nat Commun[J] 2020, 11(1):3259.

  27. Nejman D, Livyatan I, Fuks G et al. The human tumor microbiome is composed of tumor type-specific intracellular bacteria. Science[J] 2020, 368(6494):973–80.

  28. Callahan BJ, McMurdie PJ, Rosen MJ et al. DADA2: high-resolution sample inference from Illumina amplicon data. Nat Methods[J] 2016, 13(7):581–3.

  29. Bolyen E, Rideout JR, Dillon MR et al. Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nat Biotechnol[J] 2019, 37(8):852–7.

  30. Asshauer KP, Wemheuer B, Daniel R et al. Tax4Fun: predicting functional profiles from metagenomic 16S rRNA data. Bioinformatics[J] 2015, 31(17):2882–4.

  31. Abete P, Della-Morte D, Gargiulo G et al. Cognitive impairment and cardiovascular diseases in the elderly. A heart-brain continuum hypothesis. Ageing Res Rev[J] 2014, 18:41–52.

  32. Akbari E, Asemi Z, Daneshvar Kakhaki R, et al. Effect of Probiotic supplementation on cognitive function and metabolic status in Alzheimer’s Disease: a Randomized, double-blind and controlled trial. Front Aging Neurosci[J]. 2016;8:256.

    Article  PubMed  Google Scholar 

  33. Kihara Y, Yokomizo H, Murotani K. Impact of acute cholecystitis comorbidity on prognosis after surgery for gallbladder cancer: a propensity score analysis. World J Surg oncology[J] 2023, 21(1):109.

  34. Yang P, Deng KL, Zhou P et al. [Effect of macrophage-derived exosomes on promoting hepatic stellate cell activation and platelet-derived growth factor expression]. Zhonghua Gan Zang Bing Za Zhi = Zhonghua ganzangbing zazhi = Chinese journal of hepatology[J]. 2022, 30(11):1182–7.

  35. Thajudeen J, Yousuf J, Veetil VP et al. Nitrogen fixing bacterial diversity in a tropical estuarine sediments. World J Microbiol biotechnology[J] 2017, 33(2):41.

  36. Mora-Guzmán I, Martín-Pérez E. Perforated emphysematous cholecystitis and Streptococcus bovis. Revista espanola de enfermedades digestivas[J]. 2019, 111(2):166–7.

  37. Mintz D, Salamon H, Mintz M et al. Intraepithelial neutrophils in mammary, urinary and gall bladder infections. Veterinary research[J] 2019, 50(1):56.

  38. Shafagh S, Rohani SH, Hajian A. Biliary infection; distribution of species and antibiogram study. Ann Med Surg (Lond)[J]. 2021;70:102822.

    Article  Google Scholar 

  39. Molinero N, Ruiz L, Milani C et al. The human gallbladder microbiome is related to the physiological state and the biliary metabolic profile. Microbiome[J] 2019, 7(1):100.

  40. Shen H, Ye F, Xie L, et al. Metagenomic sequencing of bile from gallstone patients to identify different microbial community patterns and novel biliary bacteria. Sci Rep[J]. 2015;5:17450.

    Article  CAS  PubMed  Google Scholar 

  41. Kujiraoka M, Kuroda M, Asai K, et al. Comprehensive Diagnosis of Bacterial Infection Associated with Acute Cholecystitis using Metagenomic Approach. Front Microbiol[J]. 2017;8:685.

    Article  PubMed  Google Scholar 

  42. Gu XX, Zhang MP, Zhao YF et al. Clinical and microbiological characteristics of patients with biliary disease. World J Gastroenterol[J] 2020, 26(14):1638–46.

  43. Lee JM, Kang JS, Choi YJ et al. Suggested use of empirical antibiotics in acute cholecystitis based on bile microbiology and antibiotic susceptibility. HPB (Oxford)[J]. 2023, 25(5):568–76.

  44. Lupp C, Robertson ML, Wickham ME, et al. Host-mediated inflammation disrupts the intestinal microbiota and promotes the overgrowth of Enterobacteriaceae. Cell Host Microbe[J]. 2007;2(3):204.

    Article  CAS  PubMed  Google Scholar 

  45. Windahl U, Holst BS, Nyman A et al. Characterisation of bacterial growth and antimicrobial susceptibility patterns in canine urinary tract infections. BMC Vet Res[J] 2014, 10:217.

  46. Brower-Sinning R, Zhong D, Good M et al. Mucosa-associated bacterial diversity in necrotizing enterocolitis. PLoS One[J] 2014, 9(9):e105046.

  47. Paavonen J, Valtonen VV, Kasper DL et al. Serological evidence for the role of Bacteroides fragilis and enterobacteriaceae in the pathogenesis of acute pelvic inflammatory disease. Lancet[J] 1981, 1(8215):293–5.

  48. Liu J, Yan Q, Luo F et al. Acute cholecystitis associated with infection of Enterobacteriaceae from gut microbiota. Clin Microbiol Infect[J]. 2015, 21(9):851 e851-859.

  49. Powers SJ, Castell N, Vistein R, et al. Bacterial cholecystitis and Cholangiohepatitis in Common marmosets (Callithrix jacchus). Comp Med[J]. 2023;73(2):173–80.

    Article  CAS  PubMed  Google Scholar 

  50. Peng Y, Yang Y, Liu Y et al. Cholesterol gallstones and bile host diverse bacterial communities with potential to promote the formation of gallstones. Microb Pathog[J] 2015, 83–84:57–63.

  51. Suh SW, Choi YS, Choi SH et al. Antibiotic selection based on microbiology and resistance profiles of bile from gallbladder of patients with acute cholecystitis. Sci Rep[J] 2021, 11(1):2969.

  52. Sharma RK, Mishra K, Farooqui A et al. (1)H nuclear magnetic resonance (NMR)-based serum metabolomics of human gallbladder inflammation. Inflamm Res[J] 2017, 66(1):97–105.

  53. Watanabe M, Suliman ME, Qureshi AR et al. Consequences of low plasma histidine in chronic kidney disease patients: associations with inflammation, oxidative stress, and mortality. Am J Clin Nutr[J] 2008, 87(6):1860–6.

  54. Yokoe M, Hata J, Takada T et al. Tokyo Guidelines. 2018: diagnostic criteria and severity grading of acute cholecystitis (with videos). J Hepatobiliary Pancreat Sci[J]. 2018, 25(1):41–54.

  55. Zhang D, Wang X, Yu J et al. A case of Vagococcus fluvialis isolated from the bile of a patient with calculous cholecystitis. BMC Infect Dis[J] 2023, 23(1):689.

  56. Darkahi B, Sandblom G, Liljeholm H, et al. Biliary microflora in patients undergoing cholecystectomy. Surg Infect (Larchmt)[J]. 2014;15(3):262–5.

    Article  Google Scholar 

  57. van den Hazel SJ, Speelman P, Tytgat GN et al. Role of antibiotics in the treatment and prevention of acute and recurrent cholangitis. Clin Infect Dis[J] 1994, 19(2):279–86.

Download references


Not applicable.


This study was supported by grants from the Scientific Research Project of Xiamen Chang Gung Hospital (CMRPG1E0908, CMRPG1E0907, CMRPG1E0905), the Xiamen Science and Technology Project Fund (3502Z20224ZD1135, 3502Z20224ZD113, 3502Z20224ZD1132), the CGMH-XMCG Joint Research Program (CMRPG1E0886, CGMH-XMCG-2022-002) and the Fujian Provincial Department of Science and Technology (GMRPG1E0221, 2020D021).

Author information

Authors and Affiliations



QZ, M-XL, M-CY, Q-WM, M-JH and C-JC contributed to conception and design of the study. QZ, M-XL, M-CY and C-JC drafted the manuscript. QZ, M-XL, M-CY, Q-WM, M-JH, C-WL, C-BC, W-HC and C-JC collected the samples and information. QZ, C-WL, C-BC, W-HC and C-JC performed the data analysis and investigation. All authors revised the manuscript, contributed to the article, and approved the submitted version.

Corresponding author

Correspondence to Chih-Jung Chang.

Ethics declarations

Ethics approval and consent to participate

An informed consent form was signed by all volunteers and all experiments were performed in accordance with the Declaration of Helsinki. The research protocol was approved by the Ethics Committee of Xiamen Chang Gung Hospital (NO. CMRPG1G0161).

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s Note

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

Electronic supplementary material

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit The Creative Commons Public Domain Dedication waiver ( applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhu, Q., Li, MX., Yu, MC. et al. Altered microbiome of serum exosomes in patients with acute and chronic cholecystitis. BMC Microbiol 24, 133 (2024).

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: