Alteration of Ascending Colon Mucosal Microbiota in Patients after Cholecystectomy

Alteration of Ascending Colon Mucosal Microbiota in Patients after Cholecystectomy | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Alteration of Ascending Colon Mucosal Microbiota in Patients after Cholecystectomy Miao-Yan Fan, You Lu, Meng-Yan Cui, Meng-Qi Zhao, Jing-Jing Wang, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3174409/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract BACKGROUND Cholecystectomy is an effective therapy for gallstones, however, the incidence of CRC has increased significantly in post-cholecystectomy (PC) patients. Whether it is related to the changed mucosal microbiota in ascending colon is still unclear. AIM To explore the association between gut microbiota and cholecystectomy. METHODS Mucosal biopsy samples were collected from 30 PC patients (the test group) with gallbladder stones and 28 healthy individuals (the control group) by colonoscopy. Subsequently, the test group was subdivided into the YMA group or SNR group(age over or under 60), DG group or NG group (with or without diarrhea) and Log group or Sht group(duration over or under 5 years) according to patients’ clinical characteristics. 16S-rRNA gene amplicon sequencing was performed and alpha diversity, beta diversity and composition analysis were determined. The Phylogenetic Investigation of Communities by Reconstruction of Unobserved States based on the Kyoto Encyclopedia of Genes and Genomes database was used to predict the function of the microbiome. RESULTS The PC patients showed similar richness and overall composition with healthy controls, but PC patients over 60 years showed a different structure than those under 60 years. At the phylum level, the richness of Bacteroidetes was significantly higher in PC patients. Similarly, the genus Bacteroides , Parabacteroides and Bilophila were remarkably more abundant in PC patients compared with the controls. In addition, the PC patients had significant enrichments in both metabolic pathways, including Lipopolysaccharide and vancomycin group antibiotics biosynthesis compared to the controls. CONCLUSION Our study suggested that mucosal microbiota was changed in PC patients, which may reveal new insight into therapeutic options for colorectal cancer and diarrhea after cholecystectomy. post-cholecystectomy ascending colon mucosal gut microbiota colorectal cancer diarrhea Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Introduction Cholecystectomy, the surgical removal of the gallbladder, is the gold standard for the treatment of symptomatic cholelithiasis, which is suitable for more than 90% of patients[ 1 ]. It’s reported that there were about 8000000 cholecystectomies in the US each year, and the number is also increasing in China year by year[ 2 , 3 ]. However, some evidences supported that cholecystectomy is related to colorectal cancer(CRC). A meta-analysis of ten cohort studies from Europe, America and China demonstrated an increased risk for CRC in PC patients and a positive relationship between ascending colon cancer and cholecystectomy[ 4 ]. The same results can also be found when subjects were stratified by age and sex[ 5 ]. However, the potential specific mechanisms are remained unknown, which may relate to the distribution of gut microbiota and bile acid metabolism. With huge number and complex functions, the gut microbiota is closely related to human health[ 6 ]. Some species were considered to be an enhancer of CRC. For example, Fusobacterium nucleatum , a common inhabitor in human’s mouth, has been proved to enrich in colorectal cancer tissues. The bacterium can influence the proliferation of CRC cells and shape the tumor microenvironment by activating Wnt target genes and NF-κB pathway, as well as inducing pro-inflammatory cytokines and repressing anticancer immune responses confirmed by cell and animal experiments [ 7 ]. Similarly, Bacteroides fragilis triggers a pro-carcinogenic multi-step inflammatory cascade by IL-17R, NF-κB and STAT3 signaling in colonic epithelial cells by secreting bacteroides fragilis toxin and thus has a potential effect in the process of polyp-adenoma-CRC[ 8 ]. In addition, when PC patients were further divided into subgroups according to colonoscopy mucosal pathology, the individuals with precancerous lesions and/or CRC showed the accumulation of same species which were from the same genera with the characteristic species of sporadic CRC[ 9 ]. However, studies have found that cholecystectomy generally decreases the size of the bile acid pool and increases the enterohepatic recirculation rates of bile acids[ 10 ]. Simultaneously, removing the gallbladder can alter the flow of bile to the intestines, indicating that bile enters the duodenum directly, independent of the timing of meals. As a result, the exposure of the bile acid pool to intestinal bacteria increases, leading to an increase in the proportion of secondary bile acids(especially deoxycholic acid and lithocholic acid) in patients’ feces[ 11 ]. Notably, these secondary bile acids have been confirmed to be carcinogenic on CRC[ 12 ]. In addition, several studies focused on gut microbiota in PC patients and found that cholecystectomy can significantly change the ecological status of intestinal bacteria[ 9 , 13 – 15 ], which may involve in diarrhea[ 14 ], CRC[ 9 ] and metabolic related diseases[ 16 – 19 ] after the operation. Therefore, cholecystectomy may disrupt the balance of bile acid metabolism and lead to gut microbiota disorder, especially in right colon[ 4 , 9 , 20 ]. But the specific changed flora is inconsistent, which may be caused by different research population, geographical factors or observation time. In addition, most of previous studies focused on analyzing fecal samples and few studies have reported the relationship between the ascending colon mucosal bacteria and cholecystectomy. In this study, we enrolled 30 PC patients and 28 healthy controls to collect their ascending mucosal tissue and performed bacterial 16S rRNA gene amplicon sequencing to explore the association between gut microbiota and cholecystectomy in the PC patients and determine the effects of age, sex and duration on intestinal microbiota in these patients. What’s more, we used molecular bioinformatics technology to predict the metabolic pathways that are involved in cholecystectomy, which may reveal new insight into therapeutic options for CRC and diarrhea after cholecystectomy. Materials and Methods Study design and sample collection A total of 58 patients who underwent a colonoscopy in the Digestive Endoscopy Center at Jiading Branch of Shanghai General Hospital (Shanghai, China) were recruited for this study. We studied 30 patients undergoing laparoscopic cholecystectomy(test group) for gallstones who were assigned to the test group and then subsequently performed subgroup analysis according to age, diarrhea and duration. A group of 20 healthy controls (HC, control group) undergoing a routine physical examination was also included, who had a similar age range and sex ratio as the test group. The inclusion criteria for the test group were as follows: undergoing cholecystectomy for gallstones, aging between 30 and 75 years old, having no enrollment in other research projects and having signed informed consent. Patients who used antibiotics or probiotics within the last 2 months, had a personal history of colon cancer, inflammatory bowel disease, and colorectal cancer and patients with diabetes, a body mass index ≥ 30 kg/m 2 or with other systemic chronic diseases were excluded. This research was approved by the research ethics boards of Shanghai General Hospital (No.【2023】252). The ascending colon samples were collected by biopsy forceps during colonoscopy in both test and control groups. All samples were frozen immediately after sampling and stored at − 80°C. DNA extraction, PCR amplification, and sequencing. All samples underwent the same procedures by the same laboratory staff for DNA extraction and PCR amplification. The sample was suspended in 790µl sterile lysis buffer (4M guanidine thiocyanate; 10% N-lauroyl sarcosine; 5% N-lauroyl sarcosine-0.1 M phosphate buffer [pH 8,0]) in a 2 ml screw cap test tube containing 1 g of glass beads (0.1 mm BioSpec Products, Inc., USA). This mixture was whirled then vigorously incubate at 70°C for 1 hour. After incubation, beating the beads for 10min at maximum speed. DNA was extracted, following manufacturer's instructions for the extraction of bacterial DNA using the E.Z.N.A.Stool DNA Kit (Omega Bio-tek, Inc., GA), which except for the lysis steps and stored at − 20°C for further analysis. DNA extracted from each sample was used as a template to amplify the V3 ~ V4 region of 16S rRNA genes. The primers F1 and R2 (5’ -CCTACGGGNGGCWGCAG − 3’ and 5’-GACTACHVGGGTATCTAATCC − 3’) correspond to positions 341 to 805 in the Escherichia coli 16S rRNA gene were used to amplify the V3 ~ V4 region of each sample by PCR. PCR reactions were run in a EasyCycler 96 PCR system (Analytik Jena Corp., AG) using the following program: 3 min of denaturation at 95 ℃ followed by 21 cycles of 0.5 min at 94 ℃ (denaturation), 0.5 min for annealing at 58℃, and 0.5min at 72 ℃(elongation), with a final extension at 72 ℃ for 5min. Shanghai Mobio Biomedical Technology Co. Ltd. indexed and mixed products from different samples for sequencing in equal ratios using the Miseq platform (Illumina Inc., USA) according to the manufacturer's instructions. Data availability Raw sequencing data of the 16S rRNA gene V3–V4 regions and accompanying information are available in Sequence Read Archive database under accession number PRJNA938946. Bioinformatics and statistical analysis The pure data was extracted from the raw data using the USEARCH function (version 11.0.667) according to the following criteria: (i) The sequences of each sample were extracted using each index with zero mismatch. (ii) Sequences with an overlap of less than 16 basis points were discarded. (iii) An error rate of more than 0.1 overlap was discarded. (iv) Sequences of less than 400bp after connection were discarded. The quality-filtered sequences were grouped into unique sequences and sorted in decreasing order to identify representative sequences using UPARSE according to the UPARSE OTU analysis tube, and individual sequences were excluded at this stage. The operational taxonomic unit (OTU) was classified on the basis of 97% similarity after the removal of chimeric sequences using UPARSE (version 7.1 http://drive5.com/uparse/ ), and annotated using the SILVA reference database (SSU138). Alpha diversity metrics (ACE estimator, Chao 1 estimator, Shannon-Wiener diversity index and Simpson diversity index) were evaluated using Mothur v1.42.1. The non-parametric Mann-Whitney U test was used to test significant differences between the two groups. To compare several groups, a non-parametric Kruskal-Wallis test was used. The difference between both Bray-Curtis, weighted and unweighted UniFrac was calculated in QIIME. Principal coordinate analysis (PCoA) plots and PERMANOVA, which were used to test statistical significance between groups using 10,000 permutations, were generated R (version 3.6.0) in a package of vegan 2.5-7. The size of the linear discriminatory analysis (LDA) effect (LEfSe) was used to identify taxa of varying numbers in groups (lefse 1.1, https://github.com/SegataLab/lefse ). PICRUSt2 v2.4.1 ( https://github.com/picrust/picrust2/wiki ) was used to predict functional abundance based on 16S rRNA gene sequences. Results Clinical characteristics summary In this study, 30 PC patients and 28 healthy controls were included. In addition, subgroup analysis was carried out in PC patients according to age(YMA: age ≤ 60, n = 17; SNR: age༞60, n = 13), diarrhea(DG: diarrhea, n = 14; NG: no diarrhea, n = 16) and time after operation(Lon: ≥5 years, n = 16; Sht: ༜5 years, n = 14). Clinical characteristics of patients(test group, n = 28) and healthy controls(control group, n = 28) were shown in Table 1 . Table 1 Clinical Characteristics Summary Variable Test group (N = 28) Control group (N = 28) P value Age(mean ± SD) 56.39 ± 10.01 53.43 ± 10.41 0.282 Gender 0.591 Female 14(50%) 17(60.71%) Male 14(50%) 11(39.29%) BMI 23.79 ± 1.39 23.74 ± 1.16 0.888 History of smoking; yes 9(32.14%) 3(10.71%) 0.101 History of diarrhea; yes 14(50%) 4(14.26%) 0.009 Years after cholecystectomy (mean ± SD) 7.08 ± 6.67 - - Note: Mean age and mean BMI were expressed by (mean ± standard deviation) Abbreviations: BMI: Body Mass Index Comparison of diversity and richness in the test and control groups Using 97% as the similarity cutoff, we generated 747 OTUs. The Venn diagram showed that 569 of the 747 OTUs were shared by both groups, whereas 111 OTUs were unique to the test group, and 67 were specific to the control group(Fig. 1a). The mean observed OTUs in the single sample from the test group and control group were 201 and 212 respectively, showing that the control group had a tendency for higher OTUs, but without significant differences(Fig. 1b). The alpha diversity of the ascending colon mucosal microflora in the test group was similar to the control group. As estimated by ACE, Chao, Shannon and Simpson indexes, there were no significant differences between the two groups (Fig. 1c-f). To assess the similarities of all the samples, ecological distances were visualized using the PCoA plot, which was calculated based on Weighted UniFrac distances. PCoA, based on the relative abundance of OTUs, showed that the sample points of the test group and the control group were mixed together, indicating that the sample points of the two groups was similar as a whole. In addition, Adonis' analysis showed that there were no significant differences between the two groups (P＞0.05, Fig. 2a). In addition, a nonmetric multidimensional scaling analysis based on Weighted UniFrac distances showed that the bacterial microbiota structures of the two groups were similar (Fig. 2b). Differences of composition in the test and control groups A total of 20 phyla were detected by classifying the species of all OTUs in the ascending colon mucosa. At the phylum level, the gut microbiota of both groups was dominated by Firmicutes , followed by Bacteroidetes and Proteobacteria . The proportions of dominant flora in the test group were 33.06%, 26.96%, and 25.71% respectively, while those of the control group were 36.03%, 18.56%, and 30.80%, respectively(Figure 3a). At the genus level, the gut microbiota was dominated by Bacteroides in the control group, followed by Acinetobacter, Dietzia, Escherichia-Shigella and Ruminococcus torques group with proportions of 11.56% , 10.58% , 8.90%, 7.50%, and 6.18%, respectively. Correspondingly, Bacteroides was the most dominant bacteria in the test group, followed by Acinetobacter, Escherichia-Shigella, Dietzia and Faecalibacterium , with proportions of 19.08%, 8.11%, and 7.42%, 5.79% and 5.00%, respectively(Fig. 3b). Significant differences were found in the microbial composition between the test and control groups using the Wilcoxon rank-sum test. At the phylum level, Bacteroidetes were significantly higher in the test group compared to the control group. At the genus level, the number of Bacteroides , Parabacteroides , Lachnoclostridium and Tyzzerella was significantly higher in the test group than in the control group. Conversely, the abundances of Enterobacteriaceae_unclassified, Erysipelotrichaceae UCG-003, Elizabethkingia, Clostridia UCG-014, Cloacibacterium and Howardella were significantly lower in the test group than in the control group(Fig. 4a and 4b). A LEfSe analysis showed that the abundances of various genera, including Clostridia UCG-014, Enterobacteriaceae unclassified , Erysipelotrichaceae UCG-003, Cutibacterium, Elizabethkingia and Adlercreutzia , were significantly higher in the control group than in the test group. Conversely, the abundances of Bacteroides, Parabacteroides, Lachnoclostridium, Tyzzerell and Bilophila were higher in the test group(Fig. 4c). As showed by heatmap, a total of 14 OTUs were found to be different between the sample groups, including Clostridia_UCG-014, Tyzzerella, Oscillibacter, Cutibacterium, Bilophila, Parabacteroides, Bifidobacterium, Erysipelotrichaceae UCG-003, Achromobacter, Bacteroides, Dietzia, Butyricicoccaceae, Peptostreptococcaceae and Enterobacteriaceae unclassified (Fig. 4d). Subgroup analysis of PC patients To further determine the effect of age, diarrhea and duration on gut microbiota, we subdivide the PC patients into three pairs of groups. As estimated by ACE, Chao, Shannon and Simpson indexes, Alpha diversity of intestinal microflora did not have significant differences between the three pairs of groups. Comparing the composition of the flora of different subgroups, we found that there was a significant difference in the structure of the flora of the intestinal mucosa between two groups of patients over and under 60 years of age(P=0.0314), but there was no significant difference in the organization of flora between the two groups of patients without diarrhea or diarrhea, and between the two groups of patients more than 5 years after surgery and less than 5 years after surgery(P＞0.05, Fig. 5). The Wilcoxon rank-sum test was performed to identify specific bacteria in subgroups. There were no significant differences of phylum found between the three pair of groups. However, at the genus level, some bacteria differed between the groups. In the YMA and SNR groups, Subdoligranulum, Cloacibacillus, Megamonas, Ruminococcus, Holdemanella, Christensenellaceae R-7 group and Eubacterium siraeum group were significantly higher in the YMA group than those in the SNR group. In the DG and NG groups, the number of Corynebacterium was significantly higher in the NG group than in the DG group. Conversely, the abundances of Ruminococcus, Christensenellaceae R-7 group and Tyzzerella were significantly higher in the DG group. In the Lon and Sht groups, the abundances of Christensenellaceae R-7 group, Tyzzerella and Eubacterium siraeum group were significantly higher in the Sht group than in the Lon group(Fig. 6 Functional alterations of gut microbiomes in the test and control groups The 16S sequencing data were based on KEGG pathway database for functional prediction, and then through LEfSe analysis, the metabolic pathways (L3 level) with significant differences between the two groups were selected. The selected metabolic pathways in the figure had significant P value and LDA≥3.0.The results demonstrated that glycan degradation, Biosynthesis of vancomycin group antibiotics, Glycosaminoglycan degradation, Lipopolysaccharide biosynthesis, Selenocompound metabolism, Protein digestion and absorption were significantly higher in test group in the comparison of control group. However, Pyruvate metabolism, Dioxin degradation, Sulfur relay system, Xylene degradation were all significantly accumulated in the control group (Fig. 7). Discussion Cholecystectomy is a common surgical procedure. At present, many studies have found that the incidence of colon cancer increases with the extension of cholecystectomy time[9, 21], which is associated with altered gut microbiota and disturbed bile acid metabolism[12]. However, most of studies focused on the detection of stool samples. But fecal samples may contain transient organisms that may not reflect the mucosa-associated microbiota. As we know, adherent bacteria might be more prone to affect gene expression in colon mucosal cells than transient bacteria that are expelled in the feces. Meanwhile, the specific changed flora is inconsistent. And its impact on health is still unclear. Deoxycholic acid (DCA) and some pathogenic bacteria are considered to be tumorigenic[12, 22]. Previous study has suggested that secondary bile acids concentration were higher in the right colon [23] and an increased rate of right CRC after cholecystectomy was also observed[4, 9, 20]. In this study, there were no differences in α diversity and the overall composition of the flora between the two groups. Bacteroidetes, Parabacteroides and Bilophila were significantly higher in the test group. In addition, the metabolic pathways of Lipopolysaccharide biosynthesis and biosynthesis of vancomycin group antibiotics were enriched in the test compared to the control group. Our study found that the number of OTUs was lower in the test group compared to the control group, but not significant. Meanwhile, alpha diversity was not significantly different between the two groups, and Beta diversity based on multiple indexes indicated that the two groups were similar in overall flora composition, which is consistent with data from Korea and Russia[15, 24]. However, other studies found different results. Li et al . found reduced Beta diversity in the PC group and microbiota abundance differed between the PC and HC groups[14]; Ren et al . and Wang et al . concluded that cholecystectomy altered the microbiota of patients because they showed significant differences in flora composition between groups by Adonis test[9, 21]. A study that included 580 pairs of samples found cholecystectomy decreased microbial richness and altered flora composition in the PC group[25]. However, these studies collected fecal samples, whereas we collected mucosal specimens from the ascending colon, which may have led to different conclusions. Since the occurrence of CRC is age-related, and Kim et al .[26] found that age >60 years was an significant risk factor for the development of gastrointestinal cancer in post-cholecystectomy patients. Therefore, we further divided the PC group into ≤60 years and >60 years groups according to age and found a significant difference in the composition of the flora, suggesting that as the duration after cholecystectomy increased, a more remarkable change in bacterial composition occurred. In addition, To investigate the relationship between postoperative diarrhea and intestinal flora, we further divided the test group into diarrhea group (DG) and no diarrhea group (NG). We found similar flora richness and structure in both groups. However, Xu et al .[27]found that the abundance and homogeneity of intestinal flora were significantly lower in DG group compared with NG group, as well as a significant difference in the composition of intestinal flora, which may be related to the elevated secondary bile acids concentration after cholecystectomy. The accumulation of secondary bile acids in colon stimulates colonic 5-HT and increases colon motility, leading to diarrhea[28]. Similar findings were found by Li et al [14]and Kang et al [29]. This is different from our findings and factors such as different sampling sites and observation time may explain the differences. In our study, the control group was dominated by the Firmicutes, followed by Proteobacteria and Bacteroidetes and the results were consistent with other studies[30]. To further determine the different flora, we performed Mann Whitney U test, LEfSe analysis and random forest model and found that Bacteroidetes, Bacteroides, Parabacteroides, Bilophila were significantly higher in the PC group. In the test group, at the phylum level, the proportion of the Bacteroidetes was significantly higher, which is consistent with previous studies[13]. The members of the Bacteroidetes have been considered to be involved in immune and metabolic processes[31], which is a promoter of CRC[14]. At the genus level, we found the accumulation of Bacteroides and Parabacteroides in the PC group, in agreement with Ren et al [9]. Some species of Bacteroides , such as B. fragilis and B. vulgatus , hydrolyze taurine conjugated bile acids by bile salt hydrolases (BSHs), the detoxification of bile acids. However, free taurine can be metabolized to hydrogen sulfide(H 2 S), which can increase the colonocytes turnover and may relate to the development of CRC[32]. Especially Bacteroides fragilis was found to be more abundant in the mucosa of later-staged CRC than nearby non-cancerous tissue[33]. Moreover, Enterotoxigenic Bacteroides fragilis (ETBF) produces B. fragilis toxin (BFT) to stimulate cleavage of the tumor-suppressor protein E-cadherin and increase epithelial cell permeability by binding to colonic epithelial cells[34]. Parabacteroides distasonis is the major specie of Parabacteroides [35]. P. distasonis is reported to deconjugate bile acid salts and transform primary bile acids into secondary bile acids[36]. Although some kinds of secondary bile acids are confirmed to have a carcinogenic effects on CRC[12], Koh et al. proved that P. distasonis has anti-inflammatory and anti-cancer properties by suppressing TLR4 and Akt signaling, as well as promotion of apoptosis. Thus, further work needs to determine the relationship between Parabacteroides and tumors[37]. Based on LEfSe analysis, we found that Bilophila, a representative of Proteobacteria and Desulfovibrionaceae , was remarkably accumulated in the PC patients. Knowned as sulfate-reducing bacteria (SRB)[38] , Bilophila can produce H 2 S primarily from the degradation of cysteine. Since H 2 S is a genotoxic compound that has been shown to damage DNA leading to genomic or chromosomal instability, these H 2 S producing bacteria have an increased relative abundance in CRC[39]. Metabolic pathway, such as the Lipopolysaccharide biosynthesis was enriched in the test group, which was consistent with the research results of Wang [21]. Lipopolysaccharide (LPS), namely endotoxin, is a component of the outer membrane of gram-negative bacteria. After binding to LPS-binding protein (LBP), LPS interacts with CD14 and toll like receptor 4 (TLR4) on the membrane of cells, including monocytes, macrophages that activate intracellular signal transduction pathways and produce inflammatory factors such as TNF, IL-1 and IL-6 to induce inflammatory response[40]. Overexpression of this pathway will cause inflammation of intestinal epithelial cells and promote the progress of IBD[41]. In addition, we observed biosynthesis of vancomycin group antibiotics was significantly higher in PC patients. The metabolites involved in antibiotics biosynthesis have been found to be increased in CRC tissues, suggesting a role of microbiota structure and composition in colorectal carcinogenesis[42]. In NG patients, lipid metabolism can also be found to be enriched, which can explain why DG patients who eat too much fat often have diarrhea[14]. In conclusion, by comparing the ascending mucosal bacteria between post-cholecystectomy patients and healthy individuals, we reported mucosal bacterial dysbiosis in patients after cholecystectomy due to the alteration of flora composition based on Wilcoxon rank-sum test and LEfSe. Particularly, we found age notably affected the bacterial composition in PC patients. We subsequently noticed some specific bacteria have been changed between the groups, which may relate to colorectal cancer after cholecystectomy. Moreover, we used PICRUSTs to predict the metabolic pathways and discovered some of pathways remarkably changed in PC patients. Thus, our study provided a new insight into mechanism and therapeutics that could target the intestinal flora to attenuate related-diseases after cholecystectomy. However, there exist some limitations in our study. First, the size of sample was not large enough. Second, it’s a retrospective and single-center research. Third, we only analyzed the differences of microbiota between patients with or without cholecystectomy, and no further analysis of causality as well as related mechanism. Additionally, we analyzed at the genus level, ignoring the discrepancy of different species among the same genus. Therefore, a prospective study in a larger scale is needed to find potential correlation between microbiota alteration and post-cholecystectomy syndrome, especially CRC. Future studies should use omics data to research intestinal microbiome, which may give more opportunities to expound the mechanism of increasing incidence of colon cancer after cholecystectomy. Declarations Ethics approval and consent to participate This study was approved by the ethics committee of Shanghai General Hospital (approval No. 【2023】252). We certify that the study was performed in accordance with the 1964 declaration of HELSINKI and later amendments. Written informed consent was obtained from all subjects and/or their legal guardians prior to the enrollment of this study. Availability of data and materials The 16S rRNA sequence data generated in this study have been deposited in the Sequence Read Archive database under accession number PRJNA938946. The URL is as follows: https://dataview.ncbi.nlm.nih.gov/object/PRJNA938946?reviewer=2d2mr5apu9st95am6n7jlf94r5. Now the data has been uploaded but not been public. The data will not be available until paper being accepted. Consent for publication Not Applicable. Funding This work was supported by the Shanghai Natural Science Foundation Project (Grant No.22ZR1453500) and the fifth batch of medical key disciplines in Jiading District, Shanghai (2020‑jdyxzdxk‑15). Competing interests All authors claimed no conflicts of interests. Author’s contributions All authors were involved in patients’ enrollment, performing the study, acquisition of data and interpretation of study results. Miao-Yan Fan and You-Lu drafted the manuscript. Ying‑Ying Lu and Qiao-Li Jiang were involved in the study design and critical revision of the manuscript. All authors approved the final version of the manuscript, including the authorship list. Author details 1 Shanghai Key Laboratory of Pancreatic Disease, Shanghai JiaoTong University School of Medicine, Shanghai, China 2 Department of Gastroenterology, Shanghai General Hospital, Shanghai JiaoTong University School of Medicine, Shanghai, China 3 Department of Gastroenterology, Jiading branch of Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China References Portincasa P, Di Ciaula A, de Bari O, Garruti G, Palmieri V, Wang D-H. Management of gallstones and its related complications. Expert Rev Gastroenterol Hepatol. 2016;10:93–112. Brescia A, Gasparrini M, Nigri G, Cosenza UM, Dall’Oglio A, Pancaldi A, et al. 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Bile acid metabolism by fresh human colonic contents: a comparison of caecal versus faecal samples. Gut. 2001;49:835–42. Grigor’eva I, Romanova T, Naumova N, Alikina T, Kuznetsov A, Kabilov M. Gut Microbiome in a Russian Cohort of Pre- and Post-Cholecystectomy Female Patients. J Pers Med. 2021;11:294. Frost F, Kacprowski T, Rühlemann M, Weiss S, Bang C, Franke A, et al. Carrying asymptomatic gallstones is not associated with changes in intestinal microbiota composition and diversity but cholecystectomy with significant dysbiosis. Sci Rep. 2021;11:6677. Kim SB, Kim KO, Kim TN. Prevalence and Risk Factors of Gastric and Colorectal Cancer after Cholecystectomy. J Korean Med Sci. 2020;35:e354. Xu Y, Jing H, Wang J, Zhang S, Chang Q, Li Z, et al. Disordered Gut Microbiota Correlates With Altered Fecal Bile Acid Metabolism and Post-cholecystectomy Diarrhea. Front Microbiol. 2022;13:800604. Xu Y, Wang J, Wu X, Jing H, Zhang S, Hu Z, et al. Gut microbiota alteration after cholecystectomy contributes to post-cholecystectomy diarrhea via bile acids stimulating colonic serotonin. Gut Microbes. 2023;15:2168101. Kang Z, Lu M, Jiang M, Zhou D, Huang H. Proteobacteria Acts as a Pathogenic Risk-Factor for Chronic Abdominal Pain and Diarrhea in Post-Cholecystectomy Syndrome Patients: A Gut Microbiome Metabolomics Study. Med Sci Monit. 2019;25:7312–20. Anwar H, Iftikhar A, Muzaffar H, Almatroudi A, Allemailem KS, Navaid S, et al. Biodiversity of Gut Microbiota: Impact of Various Host and Environmental Factors. BioMed Res Int. 2021;2021:5575245. Lv L-X, Fang D-Q, Shi D, Chen D-Y, Yan R, Zhu Y-X, et al. Alterations and correlations of the gut microbiome, metabolism and immunity in patients with primary biliary cirrhosis: Gut microbiome in PBC patients. Environ Microbiol. 2016;18:2272–86. Gérard P. Metabolism of Cholesterol and Bile Acids by the Gut Microbiota. Pathogens. 2013;3:14–24. Boleij A, Hechenbleikner EM, Goodwin AC, Badani R, Stein EM, Lazarev MG, et al. The Bacteroides fragilis Toxin Gene Is Prevalent in the Colon Mucosa of Colorectal Cancer Patients. Clin Infect Dis. 2015;60:208–15. Dahmus JD, Kotler DL, Kastenberg DM, Kistler CA. The gut microbiome and colorectal cancer: a review of bacterial pathogenesis. J Gastrointest Oncol. 2018;9:769–77. Falony G, Joossens M, Vieira-Silva S, Wang J, Darzi Y, Faust K, et al. Population-level analysis of gut microbiome variation. Science. 2016;352:560–4. Wang K, Liao M, Zhou N, Bao L, Ma K, Zheng Z, et al. Parabacteroides distasonis Alleviates Obesity and Metabolic Dysfunctions via Production of Succinate and Secondary Bile Acids. Cell Rep. 2019;26:222–235e5. Koh GY, Kane A, Lee K, Xu Q, Wu X, Roper J, et al. Parabacteroides distasonis attenuates toll-like receptor 4 signaling and Akt activation and blocks colon tumor formation in high-fat diet-fed azoxymethane-treated mice. Int J Cancer. 2018;143:1797–805. Waite DW, Chuvochina M, Pelikan C, Parks DH, Yilmaz P, Wagner M, et al. Proposal to reclassify the proteobacterial classes Deltaproteobacteria and Oligoflexia, and the phylum Thermodesulfobacteria into four phyla reflecting major functional capabilities. Int J Syst Evol Microbiol. 2020;70:5972–6016. Braccia DJ, Jiang X, Pop M, Hall AB. The Capacity to Produce Hydrogen Sulfide (H2S) via Cysteine Degradation Is Ubiquitous in the Human Gut Microbiome. Front Microbiol. 2021;12:705583. Tobias PS, Tapping RI, Gegner JA. Endotoxin Interactions with Lipopolysaccharide-Responsive Cells. Clin Infect Dis. 1999;28:476–81. Yang L, Wu G, Wu Q, Peng L, Yuan L. METTL3 overexpression aggravates LPS-induced cellular inflammation in mouse intestinal epithelial cells and DSS-induced IBD in mice. Cell Death Discov. 2022;8:62. Loke MF, Chua EG, Gan HM, Thulasi K, Wanyiri JW, Thevambiga I, et al. Metabolomics and 16S rRNA sequencing of human colorectal cancers and adjacent mucosa. PLoS ONE. 2018;13:e0208584. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3174409","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":223402419,"identity":"0fe6c4f1-b4a9-4d58-85e3-e9354192a4cf","order_by":0,"name":"Miao-Yan Fan","email":"","orcid":"","institution":"Shanghai General Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Miao-Yan","middleName":"","lastName":"Fan","suffix":""},{"id":223402420,"identity":"3210d5f2-e230-4b1d-8d1f-ace1db3c6d38","order_by":1,"name":"You Lu","email":"","orcid":"","institution":"Shanghai General Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"You","middleName":"","lastName":"Lu","suffix":""},{"id":223402421,"identity":"1092943e-b027-4deb-9394-aef1405a3e60","order_by":2,"name":"Meng-Yan Cui","email":"","orcid":"","institution":"Shanghai General Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Meng-Yan","middleName":"","lastName":"Cui","suffix":""},{"id":223402423,"identity":"64389766-6731-4b0e-ba6c-f8cbf428f335","order_by":3,"name":"Meng-Qi Zhao","email":"","orcid":"","institution":"Shanghai General Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Meng-Qi","middleName":"","lastName":"Zhao","suffix":""},{"id":223402425,"identity":"3955b0e2-00a4-48e4-ad1b-f5e8ec63a59a","order_by":4,"name":"Jing-Jing Wang","email":"","orcid":"","institution":"Shanghai Key Laboratory of Pancreatic Disease, Shanghai JiaoTong University School of Medicine","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Jing-Jing","middleName":"","lastName":"Wang","suffix":""},{"id":223402426,"identity":"51c92c78-aac1-4b68-ae21-971a2b2c6302","order_by":5,"name":"Qiao-Li Jiang","email":"","orcid":"","institution":"Shanghai General Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Qiao-Li","middleName":"","lastName":"Jiang","suffix":""},{"id":223402427,"identity":"7908ae02-6dc4-4724-a628-8738d51bb9bb","order_by":6,"name":"Ying-Ying Lu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA3klEQVRIie3NsQrCMBCA4ZNAusS6qos+wkGhCkr7KkrBTegjBArd3B18Cwdxq9zgIvgCHQShiw51c+hgLApOMaNgfkg4wn0EwGb7xdjzQnUcgKyErJ4NCYPGbmlEPiwjYUJw36SLiPNAMoE0rvJgA6w4aQm5s5HAIqrJPC2ireQD7U9IwvfUcgQ1kRRhJnjbnAwrM+Kd1XJQE+AUfCUd9UtjhTThjMe7RUoTJO5riXs8eOW1orDlJOvyrgbcJ4WW9DPgXQEwTV8PU8l0+6qeBHa7A4Tvh1C3bbPZbP/ZAx50SgC6VxjoAAAAAElFTkSuQmCC","orcid":"","institution":"Shanghai General Hospital","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Ying-Ying","middleName":"","lastName":"Lu","suffix":""}],"badges":[],"createdAt":"2023-07-16 06:44:18","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3174409/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3174409/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":41249123,"identity":"aaf00509-d58c-4ed4-b4c6-03c93118bed6","added_by":"auto","created_at":"2023-08-08 14:49:38","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":279543,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eOperational Taxonomic Units clustering and alpha diversity analysis of mucosal intestinal microflora in test and control groups.\u003c/strong\u003e a: Venn diagram demonstrates the shared and unique Operational Taxonomic Units (OTUs) in test and control groups; b: The observed OTUs in the single sample from each group; c: ACE estimator; d: Chao index; e: Shannon-Wiener diversity index; f: Simpson diversity index.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-3174409/v1/0afbe3a471a54dee1873a3ba.png"},{"id":41247058,"identity":"75f58a2a-4a0f-4ae3-a0db-460ae2977ee1","added_by":"auto","created_at":"2023-08-08 14:41:38","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":373845,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAnalysis of beta diversity based on Operational Taxonomic Units levels in test and control groups.\u003c/strong\u003e a: Principal coordinates analysis plots based on Weighted UniFrac distances; b: Nonmetric multidimensional scaling analysis based on Weighted UniFrac distances. Each symbol represents one sample.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-3174409/v1/4a92abe042785004b9e6652a.png"},{"id":41250143,"identity":"6d0fdf7c-f268-413b-9986-a9350e4e33db","added_by":"auto","created_at":"2023-08-08 14:57:38","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":122502,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFlora composition of microbiome composition in test and control groups. \u003c/strong\u003ea: Flora composition at the phylum level; b: Flora composition at the genus level\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-3174409/v1/77ffc9dd2f3e323954686189.png"},{"id":41247053,"identity":"b39c876a-5213-43d8-88cd-1f992a86168a","added_by":"auto","created_at":"2023-08-08 14:41:37","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":271891,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFlora differences of microbiome composition in test and control groups.\u003c/strong\u003e a: The abundance of Bacteroidetes was significantly higher at the phylum level in the test group, as assessed by a Wilcoxon rank-sum test; b: Differences in the flora at the genus level between the groups, as assessed by a Wilcoxon rank-sum test; c: Flora differences at the genus level, as assessed by Linear discriminant analysis effect size; d: A heatmap analysis of the microbiomes using a random forest model.\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-3174409/v1/e205463eafd7341ed42c6a5a.png"},{"id":41247055,"identity":"80ff33d1-611f-47d8-a0f2-a4bee9424560","added_by":"auto","created_at":"2023-08-08 14:41:38","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":295168,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAnalysis of beta diversity based on Operational Taxonomic Units levels in subgroups.\u003c/strong\u003e a: Principal coordinates analysis plots based on Unweighted UniFrac distances of YMA and SNR groups. b: Principal coordinates analysis plots based on Bray-Curtis distances of DG and NG groups. c: Principal coordinates analysis plots based on Unweighted Unifrac distances of Lon and Sht groups. YMA: patients over 60 years. SNR: patients under 60 years. DG: patients had diarrhea. NG: patients without diarrhea. Lon: post-operative patients over 5 years. Sht: post-operative patients less than 5 years.\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-3174409/v1/e566c1ebe3705810d5f41422.png"},{"id":41249124,"identity":"18fbb001-3c07-4f30-968a-dee5af389960","added_by":"auto","created_at":"2023-08-08 14:49:38","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":192496,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFlora differences of microbiome composition in subgroups at the genus level assessed by the Wilcoxon rank-sum test. \u003c/strong\u003ea: Differences in the flora at the genus level between the YMA and SNR groups. b: Differences in the flora at the genus level between the DG and NG groups. c: Differences in the flora at the genus level between the DG and NG groups. YMA: patients over 60 years. SNR: patients under 60 years. DG: patients had diarrhea. NG: patients without diarrhea. Lon: post-operative patients over 5 years. Sht: post-operative patients less than 5 years.\u003c/p\u003e","description":"","filename":"Figure6.png","url":"https://assets-eu.researchsquare.com/files/rs-3174409/v1/e159535e14d0442902909a05.png"},{"id":41247059,"identity":"69977b13-d606-458a-b5bb-a052106413eb","added_by":"auto","created_at":"2023-08-08 14:41:38","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":43153,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAltered metabolic pathways as shown by the histogram of the LDA scores between the test and control groups.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Figure7.png","url":"https://assets-eu.researchsquare.com/files/rs-3174409/v1/00497cecbe02eef753f8fbc9.png"},{"id":51998461,"identity":"faadc1e8-722c-4c9b-ab4b-e53ed16228d0","added_by":"auto","created_at":"2024-03-05 06:55:11","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1976023,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3174409/v1/8deb91b5-4e8f-4b07-858b-de47fee66083.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Alteration of Ascending Colon Mucosal Microbiota in Patients after Cholecystectomy","fulltext":[{"header":"Introduction","content":"\u003cp\u003eCholecystectomy, the surgical removal of the gallbladder, is the gold standard for the treatment of symptomatic cholelithiasis, which is suitable for more than 90% of patients[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. It\u0026rsquo;s reported that there were about 8000000 cholecystectomies in the US each year, and the number is also increasing in China year by year[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. However, some evidences supported that cholecystectomy is related to colorectal cancer(CRC). A meta-analysis of ten cohort studies from Europe, America and China demonstrated an increased risk for CRC in PC patients and a positive relationship between ascending colon cancer and cholecystectomy[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. The same results can also be found when subjects were stratified by age and sex[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. However, the potential specific mechanisms are remained unknown, which may relate to the distribution of gut microbiota and bile acid metabolism.\u003c/p\u003e \u003cp\u003eWith huge number and complex functions, the gut microbiota is closely related to human health[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Some species were considered to be an enhancer of CRC. For example, \u003cem\u003eFusobacterium nucleatum\u003c/em\u003e, a common inhabitor in human\u0026rsquo;s mouth, has been proved to enrich in colorectal cancer tissues. The bacterium can influence the proliferation of CRC cells and shape the tumor microenvironment by activating Wnt target genes and NF-κB pathway, as well as inducing pro-inflammatory cytokines and repressing anticancer immune responses confirmed by cell and animal experiments [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Similarly, \u003cem\u003eBacteroides fragilis\u003c/em\u003e triggers a pro-carcinogenic multi-step inflammatory cascade by IL-17R, NF-κB and STAT3 signaling in colonic epithelial cells by secreting bacteroides fragilis toxin and thus has a potential effect in the process of polyp-adenoma-CRC[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. In addition, when PC patients were further divided into subgroups according to colonoscopy mucosal pathology, the individuals with precancerous lesions and/or CRC showed the accumulation of same species which were from the same genera with the characteristic species of sporadic CRC[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eHowever, studies have found that cholecystectomy generally decreases the size of the bile acid pool and increases the enterohepatic recirculation rates of bile acids[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Simultaneously, removing the gallbladder can alter the flow of bile to the intestines, indicating that bile enters the duodenum directly, independent of the timing of meals. As a result, the exposure of the bile acid pool to intestinal bacteria increases, leading to an increase in the proportion of secondary bile acids(especially deoxycholic acid and lithocholic acid) in patients\u0026rsquo; feces[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Notably, these secondary bile acids have been confirmed to be carcinogenic on CRC[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. In addition, several studies focused on gut microbiota in PC patients and found that cholecystectomy can significantly change the ecological status of intestinal bacteria[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan additionalcitationids=\"CR14\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], which may involve in diarrhea[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], CRC[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] and metabolic related diseases[\u003cspan additionalcitationids=\"CR17 CR18\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] after the operation. Therefore, cholecystectomy may disrupt the balance of bile acid metabolism and lead to gut microbiota disorder, especially in right colon[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. But the specific changed flora is inconsistent, which may be caused by different research population, geographical factors or observation time. In addition, most of previous studies focused on analyzing fecal samples and few studies have reported the relationship between the ascending colon mucosal bacteria and cholecystectomy.\u003c/p\u003e \u003cp\u003eIn this study, we enrolled 30 PC patients and 28 healthy controls to collect their ascending mucosal tissue and performed bacterial 16S rRNA gene amplicon sequencing to explore the association between gut microbiota and cholecystectomy in the PC patients and determine the effects of age, sex and duration on intestinal microbiota in these patients. What\u0026rsquo;s more, we used molecular bioinformatics technology to predict the metabolic pathways that are involved in cholecystectomy, which may reveal new insight into therapeutic options for CRC and diarrhea after cholecystectomy.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design and sample collection\u003c/h2\u003e \u003cp\u003eA total of 58 patients who underwent a colonoscopy in the Digestive Endoscopy Center at Jiading Branch of Shanghai General Hospital (Shanghai, China) were recruited for this study. We studied 30 patients undergoing laparoscopic cholecystectomy(test group) for gallstones who were assigned to the test group and then subsequently performed subgroup analysis according to age, diarrhea and duration. A group of 20 healthy controls (HC, control group) undergoing a routine physical examination was also included, who had a similar age range and sex ratio as the test group. The inclusion criteria for the test group were as follows: undergoing cholecystectomy for gallstones, aging between 30 and 75 years old, having no enrollment in other research projects and having signed informed consent. Patients who used antibiotics or probiotics within the last 2 months, had a personal history of colon cancer, inflammatory bowel disease, and colorectal cancer and patients with diabetes, a body mass index\u0026thinsp;\u0026ge;\u0026thinsp;30 kg/m\u003csup\u003e2\u003c/sup\u003e or with other systemic chronic diseases were excluded. This research was approved by the research ethics boards of Shanghai General Hospital (No.【2023】252).\u003c/p\u003e \u003cp\u003eThe ascending colon samples were collected by biopsy forceps during colonoscopy in both test and control groups. All samples were frozen immediately after sampling and stored at \u0026minus;\u0026thinsp;80\u0026deg;C.\u003c/p\u003e \u003cp\u003e \u003cb\u003eDNA extraction, PCR amplification, and sequencing.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eAll samples underwent the same procedures by the same laboratory staff for DNA extraction and PCR amplification. The sample was suspended in 790\u0026micro;l sterile lysis buffer (4M guanidine thiocyanate; 10% N-lauroyl sarcosine; 5% N-lauroyl sarcosine-0.1 M phosphate buffer [pH 8,0]) in a 2 ml screw cap test tube containing 1 g of glass beads (0.1 mm BioSpec Products, Inc., USA). This mixture was whirled then vigorously incubate at 70\u0026deg;C for 1 hour. After incubation, beating the beads for 10min at maximum speed. DNA was extracted, following manufacturer's instructions for the extraction of bacterial DNA using the E.Z.N.A.Stool DNA Kit (Omega Bio-tek, Inc., GA), which except for the lysis steps and stored at \u0026minus;\u0026thinsp;20\u0026deg;C for further analysis. DNA extracted from each sample was used as a template to amplify the V3\u0026thinsp;~\u0026thinsp;V4 region of 16S rRNA genes. The primers F1 and R2 (5\u0026rsquo; -CCTACGGGNGGCWGCAG \u0026minus;\u0026thinsp;3\u0026rsquo; and 5\u0026rsquo;-GACTACHVGGGTATCTAATCC \u0026minus;\u0026thinsp;3\u0026rsquo;) correspond to positions 341 to 805 in the \u003cem\u003eEscherichia coli\u003c/em\u003e 16S rRNA gene were used to amplify the V3\u0026thinsp;~\u0026thinsp;V4 region of each sample by PCR. PCR reactions were run in a EasyCycler 96 PCR system (Analytik Jena Corp., AG) using the following program: 3 min of denaturation at 95 ℃ followed by 21 cycles of 0.5 min at 94 ℃ (denaturation), 0.5 min for annealing at 58℃, and 0.5min at 72 ℃(elongation), with a final extension at 72 ℃ for 5min. Shanghai Mobio Biomedical Technology Co. Ltd. indexed and mixed products from different samples for sequencing in equal ratios using the Miseq platform (Illumina Inc., USA) according to the manufacturer's instructions.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eData availability\u003c/h2\u003e \u003cp\u003eRaw sequencing data of the 16S rRNA gene V3\u0026ndash;V4 regions and accompanying information are available in Sequence Read Archive database under accession number PRJNA938946.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eBioinformatics and statistical analysis\u003c/h2\u003e \u003cp\u003eThe pure data was extracted from the raw data using the USEARCH function (version 11.0.667) according to the following criteria: (i) The sequences of each sample were extracted using each index with zero mismatch. (ii) Sequences with an overlap of less than 16 basis points were discarded. (iii) An error rate of more than 0.1 overlap was discarded. (iv) Sequences of less than 400bp after connection were discarded. The quality-filtered sequences were grouped into unique sequences and sorted in decreasing order to identify representative sequences using UPARSE according to the UPARSE OTU analysis tube, and individual sequences were excluded at this stage. The operational taxonomic unit (OTU) was classified on the basis of 97% similarity after the removal of chimeric sequences using UPARSE (version 7.1 \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://drive5.com/uparse/\u003c/span\u003e\u003cspan address=\"http://drive5.com/uparse/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), and annotated using the SILVA reference database (SSU138). Alpha diversity metrics (ACE estimator, Chao 1 estimator, Shannon-Wiener diversity index and Simpson diversity index) were evaluated using Mothur v1.42.1. The non-parametric Mann-Whitney U test was used to test significant differences between the two groups. To compare several groups, a non-parametric Kruskal-Wallis test was used. The difference between both Bray-Curtis, weighted and unweighted UniFrac was calculated in QIIME. Principal coordinate analysis (PCoA) plots and PERMANOVA, which were used to test statistical significance between groups using 10,000 permutations, were generated R (version 3.6.0) in a package of vegan 2.5-7. The size of the linear discriminatory analysis (LDA) effect (LEfSe) was used to identify taxa of varying numbers in groups (lefse 1.1, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://github.com/SegataLab/lefse\u003c/span\u003e\u003cspan address=\"https://github.com/SegataLab/lefse\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e).\u003c/span\u003e PICRUSt2 v2.4.1 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://github.com/picrust/picrust2/wiki\u003c/span\u003e\u003cspan address=\"https://github.com/picrust/picrust2/wiki\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e)\u003c/span\u003e was used to predict functional abundance based on 16S rRNA gene sequences.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\n\u003ch2\u003eClinical characteristics summary\u003c/h2\u003e\n\u003cp\u003eIn this study, 30 PC patients and 28 healthy controls were included. In addition, subgroup analysis was carried out in PC patients according to age(YMA: age\u0026thinsp;\u0026le;\u0026thinsp;60, n\u0026thinsp;=\u0026thinsp;17; SNR: age༞60, n\u0026thinsp;=\u0026thinsp;13), diarrhea(DG: diarrhea, n\u0026thinsp;=\u0026thinsp;14; NG: no diarrhea, n\u0026thinsp;=\u0026thinsp;16) and time after operation(Lon: \u0026ge;5 years, n\u0026thinsp;=\u0026thinsp;16; Sht: ༜5 years, n\u0026thinsp;=\u0026thinsp;14). Clinical characteristics of patients(test group, n\u0026thinsp;=\u0026thinsp;28) and healthy controls(control group, n\u0026thinsp;=\u0026thinsp;28) were shown in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003ctable id=\"Tab1\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eClinical Characteristics Summary\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eVariable\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eTest group (N\u0026thinsp;=\u0026thinsp;28)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eControl group (N\u0026thinsp;=\u0026thinsp;28)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eP value\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAge(mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e56.39\u0026thinsp;\u0026plusmn;\u0026thinsp;10.01\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e53.43\u0026thinsp;\u0026plusmn;\u0026thinsp;10.41\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.282\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eGender\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.591\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eFemale\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e14(50%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e17(60.71%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMale\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e14(50%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e11(39.29%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eBMI\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e23.79\u0026thinsp;\u0026plusmn;\u0026thinsp;1.39\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e23.74\u0026thinsp;\u0026plusmn;\u0026thinsp;1.16\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.888\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHistory of smoking; yes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e9(32.14%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3(10.71%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.101\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHistory of diarrhea; yes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e14(50%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4(14.26%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.009\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYears after cholecystectomy (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e7.08\u0026thinsp;\u0026plusmn;\u0026thinsp;6.67\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003ctfoot\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"4\"\u003e\n\u003cp\u003eNote: Mean age and mean BMI were expressed by (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation)\u003c/p\u003e\n\u003cp\u003eAbbreviations: BMI: Body Mass Index\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tfoot\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eComparison of diversity and richness in the test and control groups\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eUsing 97% as the similarity cutoff, we generated 747 OTUs. The Venn diagram showed that 569 of the 747 OTUs were shared by both groups, whereas 111 OTUs were unique to the test group, and 67 were specific to the control group(Fig. 1a). The mean observed OTUs in the single sample from the test group and control group were 201 and 212 respectively, showing that the control group had a tendency for higher OTUs, but without significant differences(Fig. 1b). The alpha diversity of the ascending colon mucosal microflora in the test group was similar to the control group. As estimated by ACE, Chao, Shannon and Simpson indexes, there were no significant differences between the two groups (Fig. 1c-f).\u003c/p\u003e\n\u003cp\u003eTo assess the similarities of all the samples, ecological distances were visualized using the PCoA plot, which was calculated based on Weighted UniFrac distances. PCoA, based on the relative abundance of OTUs, showed that the sample points of the test group and the control group were mixed together, indicating that the sample points of the two groups was similar as a whole. In addition, Adonis' analysis showed that there were no significant differences between the two groups (P＞0.05, Fig. 2a). In addition, a nonmetric multidimensional scaling analysis based on Weighted UniFrac distances showed that the bacterial microbiota structures of the two groups were similar (Fig. 2b).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eDifferences of composition in the test and control groups\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 20 phyla were detected by classifying the species of all OTUs in the ascending colon mucosa. At the phylum level, the gut microbiota of both groups was dominated by \u003cem\u003eFirmicutes\u003c/em\u003e, followed by \u003cem\u003eBacteroidetes\u003c/em\u003e and \u003cem\u003eProteobacteria\u003c/em\u003e. The proportions of dominant flora in the test group were 33.06%, 26.96%, and 25.71% respectively, while those of the control group were 36.03%, 18.56%, and 30.80%, respectively(Figure 3a). At the genus level, the gut microbiota was dominated by \u003cem\u003eBacteroides\u003c/em\u003e in the control group, followed by \u003cem\u003eAcinetobacter, Dietzia, Escherichia-Shigella \u003c/em\u003eand\u003cem\u003e Ruminococcus\u003c/em\u003e \u003cem\u003etorques group\u003c/em\u003e with proportions of 11.56% , 10.58% , 8.90%, 7.50%, and 6.18%, respectively. Correspondingly, \u003cem\u003eBacteroides\u003c/em\u003e was the most dominant bacteria in the test group, followed by \u003cem\u003eAcinetobacter, Escherichia-Shigella, Dietzia \u003c/em\u003eand\u003cem\u003e Faecalibacterium\u003c/em\u003e, with proportions of 19.08%, 8.11%,\u0026nbsp; and 7.42%, 5.79% and 5.00%, respectively(Fig. 3b).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSignificant differences were found in the microbial composition between the test and control groups using the Wilcoxon rank-sum test. At the phylum level, \u003cem\u003eBacteroidetes\u003c/em\u003e were significantly higher in the test group compared to the control group. At the genus level, the number of \u003cem\u003eBacteroides\u003c/em\u003e, \u003cem\u003eParabacteroides\u003c/em\u003e, \u003cem\u003eLachnoclostridium\u003c/em\u003e and\u003cem\u003e Tyzzerella\u003c/em\u003e was significantly higher in the test group than in the control group. Conversely, the abundances of \u003cem\u003eEnterobacteriaceae_unclassified, Erysipelotrichaceae UCG-003, Elizabethkingia, Clostridia UCG-014, Cloacibacterium\u003c/em\u003e and \u003cem\u003eHowardella\u003c/em\u003e were significantly lower in the test group than in the control group(Fig. 4a and 4b).\u003c/p\u003e\n\u003cp\u003eA LEfSe analysis showed that the abundances of various genera, including \u003cem\u003eClostridia UCG-014, Enterobacteriaceae unclassified , Erysipelotrichaceae UCG-003, Cutibacterium, Elizabethkingia \u003c/em\u003eand\u003cem\u003e Adlercreutzia\u003c/em\u003e, were significantly higher in the control group than in the test group. Conversely, the abundances of \u003cem\u003eBacteroides, Parabacteroides, Lachnoclostridium, Tyzzerell \u003c/em\u003eand\u003cem\u003e Bilophila\u003c/em\u003e were higher in the test group(Fig. 4c).\u003c/p\u003e\n\u003cp\u003eAs showed by heatmap, a total of 14 OTUs were found to be different between the sample groups, including\u003cem\u003e Clostridia_UCG-014, Tyzzerella, Oscillibacter, Cutibacterium, Bilophila, Parabacteroides, Bifidobacterium, Erysipelotrichaceae UCG-003, Achromobacter, Bacteroides, Dietzia, Butyricicoccaceae, Peptostreptococcaceae\u003c/em\u003e and\u003cem\u003e Enterobacteriaceae unclassified\u003c/em\u003e(Fig. 4d).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eSubgroup analysis of PC patients\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo further determine the effect of age, diarrhea and duration on gut microbiota, we subdivide the PC patients into three pairs of groups. As estimated by ACE, Chao, Shannon and Simpson indexes, Alpha diversity of intestinal microflora did not have significant differences between the three pairs of groups. Comparing the composition of the flora of different subgroups, we found that there was a significant difference in the structure of the flora of the intestinal mucosa between two groups of patients over and under 60 years of age(P=0.0314), but there was no significant difference in the organization of flora between the two groups of patients without diarrhea or diarrhea, and between the two groups of patients more than 5 years after surgery and less than 5 years after surgery(P＞0.05, Fig. 5).\u003c/p\u003e\n\u003cp\u003eThe Wilcoxon rank-sum test was performed to identify specific bacteria in subgroups. There were no significant differences of phylum found between the three pair of groups. However, at the genus level, some bacteria differed between the groups. In the YMA and SNR groups, Subdoligranulum, Cloacibacillus, Megamonas, Ruminococcus, Holdemanella, Christensenellaceae R-7 group and Eubacterium siraeum group were significantly higher in the YMA group than those in the SNR group. In the DG and NG groups, the number of Corynebacterium was significantly higher in the NG group than in the DG group. Conversely, the abundances of Ruminococcus, Christensenellaceae R-7 group and Tyzzerella were significantly higher in the DG group. In the Lon and Sht groups, the abundances of Christensenellaceae R-7 group, Tyzzerella and Eubacterium siraeum group were significantly higher in the Sht group than in the Lon group(Fig. 6\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eFunctional alterations of gut microbiomes in the test and control groups\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe 16S sequencing data were based on KEGG pathway database for functional prediction, and then through LEfSe analysis, the metabolic pathways (L3 level) with significant differences between the two groups were selected. The selected metabolic pathways in the figure had significant P value and LDA\u0026ge;3.0.The results demonstrated that glycan degradation, Biosynthesis of vancomycin group antibiotics, Glycosaminoglycan degradation, Lipopolysaccharide biosynthesis, Selenocompound metabolism, Protein digestion and absorption were significantly higher in test group in the comparison of control group. However, Pyruvate metabolism, Dioxin degradation, Sulfur relay system, Xylene degradation were all significantly accumulated in the control group (Fig. 7).\u003c/p\u003e\n\u003c/div\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eCholecystectomy is a common surgical procedure. At present, many studies have found that the incidence of colon cancer increases with the extension of cholecystectomy time[9, 21], which is associated with altered gut microbiota and disturbed bile acid metabolism[12]. However, most of studies focused on the detection of stool samples. But fecal samples may contain transient organisms that may not reflect the mucosa-associated microbiota. As we know, adherent bacteria might be more prone to affect gene expression in colon mucosal cells than transient bacteria that are expelled in the feces. Meanwhile, the specific changed flora is inconsistent. And its impact on health is still unclear. Deoxycholic acid (DCA) and some pathogenic bacteria are considered to be tumorigenic[12, 22]. Previous study has suggested that secondary bile acids concentration were higher in the right colon [23] and an increased rate of right CRC after cholecystectomy was also observed[4, 9, 20]. In this study, there were no differences in \u0026alpha; diversity and the overall composition of the flora between the two groups. \u003cem\u003eBacteroidetes, Parabacteroides\u003c/em\u003e and \u003cem\u003eBilophila \u003c/em\u003ewere significantly higher in the test group. In addition, the metabolic pathways of Lipopolysaccharide biosynthesis and biosynthesis of vancomycin group antibiotics were enriched in the test compared to the control group.\u003c/p\u003e\n\u003cp\u003eOur study found that the number of OTUs was lower in the test group compared to the control group, but not significant. Meanwhile, alpha diversity was not significantly different between the two groups, and Beta diversity based on multiple indexes indicated that the two groups were similar in overall flora composition, which is consistent with data from Korea and Russia[15, 24]. However, other studies found different results. Li \u003cem\u003eet al\u003c/em\u003e. found reduced Beta diversity in the PC group and microbiota abundance differed between the PC and HC groups[14]; Ren \u003cem\u003eet al\u003c/em\u003e. and Wang \u003cem\u003eet al\u003c/em\u003e. concluded that cholecystectomy altered the microbiota of patients because they showed significant differences in flora composition between groups by Adonis test[9, 21]. A study that included 580 pairs of samples found cholecystectomy decreased microbial richness and altered flora composition in the PC group[25]. However, these studies collected fecal samples, whereas we collected mucosal specimens from the ascending colon, which may have led to different conclusions.\u003c/p\u003e\n\u003cp\u003eSince the occurrence of CRC is age-related, and Kim \u003cem\u003eet al\u003c/em\u003e.[26] found that age \u0026gt;60 years was an significant risk factor for the development of gastrointestinal cancer in post-cholecystectomy patients. Therefore, we further divided the PC group into \u0026le;60 years and \u0026gt;60 years groups according to age and found a significant difference in the composition of the flora, suggesting that as the duration after cholecystectomy increased, a more remarkable change in bacterial composition occurred. In addition, To investigate the relationship between postoperative diarrhea and intestinal flora, we further divided the test group into diarrhea group (DG) and no diarrhea group (NG). We found similar flora richness and structure in both groups. However, Xu \u003cem\u003eet al\u003c/em\u003e.[27]found that the abundance and homogeneity of intestinal flora were significantly lower in DG group compared with NG group, as well as a significant difference in the composition of intestinal flora, which may be related to the elevated secondary bile acids concentration after cholecystectomy. The accumulation of secondary bile acids in colon stimulates colonic 5-HT and increases colon motility, leading to diarrhea[28]. Similar findings were found by Li \u003cem\u003eet al\u003c/em\u003e[14]and Kang \u003cem\u003eet al\u003c/em\u003e[29]. This is different from our findings and factors such as different sampling sites and observation time may explain the differences.\u003c/p\u003e\n\u003cp\u003eIn our study, the control group was dominated by the Firmicutes, followed by \u003cem\u003eProteobacteria\u003c/em\u003e and \u003cem\u003eBacteroidetes\u003c/em\u003e and the results were consistent with other studies[30]. To further determine the different flora, we performed Mann Whitney U test, LEfSe analysis and random forest model and found that \u003cem\u003eBacteroidetes, Bacteroides, Parabacteroides, Bilophila \u003c/em\u003ewere significantly higher in the PC group.\u003c/p\u003e\n\u003cp\u003eIn the test group, at the phylum level, the proportion of the \u003cem\u003eBacteroidetes\u003c/em\u003e was significantly higher, which is consistent with previous studies[13]. The members of the \u003cem\u003eBacteroidetes\u003c/em\u003e have been considered to be involved in immune and metabolic processes[31], which is a promoter of CRC[14]. At the genus level, we found the accumulation of \u003cem\u003eBacteroides\u003c/em\u003e and \u003cem\u003eParabacteroides\u003c/em\u003e in the PC group, in agreement with Ren\u003cem\u003e et al\u003c/em\u003e[9]. Some species of \u003cem\u003eBacteroides\u003c/em\u003e, such as\u003cem\u003e B. fragilis\u003c/em\u003e and \u003cem\u003eB. vulgatus\u003c/em\u003e, hydrolyze taurine conjugated bile acids by bile salt hydrolases (BSHs), the detoxification of bile acids. However, free taurine can be metabolized to hydrogen sulfide(H\u003csub\u003e2\u003c/sub\u003eS), which can increase the colonocytes turnover and may relate to the development of CRC[32]. Especially \u003cem\u003eBacteroides fragilis\u003c/em\u003e was found to be more abundant in the mucosa of later-staged CRC than nearby non-cancerous tissue[33]. Moreover,\u003cem\u003e Enterotoxigenic\u003c/em\u003e\u003cem\u003eBacteroides fragilis\u003c/em\u003e (ETBF) produces B. fragilis toxin (BFT) to stimulate cleavage of the tumor-suppressor protein E-cadherin and increase epithelial cell permeability by binding to colonic epithelial cells[34].\u003cem\u003e Parabacteroides distasonis\u003c/em\u003e is the major specie of \u003cem\u003eParabacteroides\u003c/em\u003e[35]. \u003cem\u003eP.\u003c/em\u003e\u003cem\u003edistasonis \u003c/em\u003eis reported to deconjugate bile acid salts and transform primary bile acids into secondary bile acids[36]. Although some kinds of secondary bile acids are confirmed to have a carcinogenic effects on CRC[12], Koh et al. proved that \u003cem\u003eP. distasonis\u003c/em\u003e has anti-inflammatory and anti-cancer properties by suppressing TLR4 and Akt signaling, as well as promotion of apoptosis. Thus, further work needs to determine the relationship between \u003cem\u003eParabacteroides\u003c/em\u003e and tumors[37].\u003c/p\u003e\n\u003cp\u003eBased on LEfSe analysis, we found that\u003cem\u003e Bilophila, \u003c/em\u003ea representative of \u003cem\u003eProteobacteria\u003c/em\u003e and \u003cem\u003eDesulfovibrionaceae\u003c/em\u003e, was remarkably accumulated in the PC patients. Knowned as sulfate-reducing bacteria (SRB)[38] , \u003cem\u003eBilophila\u003c/em\u003e can produce H\u003csub\u003e2\u003c/sub\u003eS primarily from the degradation of cysteine. Since H\u003csub\u003e2\u003c/sub\u003eS is a genotoxic compound that has been shown to damage DNA leading to genomic or chromosomal instability, these H\u003csub\u003e2\u003c/sub\u003eS producing bacteria have an increased relative abundance in CRC[39].\u003c/p\u003e\n\u003cp\u003eMetabolic pathway, such as the Lipopolysaccharide biosynthesis was enriched in the test group, which was consistent with the research results of Wang [21]. Lipopolysaccharide (LPS), namely endotoxin, is a component of the outer membrane of gram-negative bacteria. After binding to LPS-binding protein (LBP), LPS interacts with CD14 and toll like receptor 4 (TLR4) on the membrane of cells, including monocytes, macrophages that activate intracellular signal transduction pathways and produce inflammatory factors such as TNF, IL-1 and IL-6 to induce inflammatory response[40]. Overexpression of this pathway will cause inflammation of intestinal epithelial cells and promote the progress of IBD[41]. In addition, we observed biosynthesis of vancomycin group antibiotics was significantly higher in PC patients. The metabolites involved in antibiotics biosynthesis have been found to be increased in CRC tissues, suggesting a role of microbiota structure and composition in colorectal carcinogenesis[42]. In NG patients, lipid metabolism can also be found to be enriched, which can explain why DG patients who eat too much fat often have diarrhea[14].\u003c/p\u003e\n\u003cp\u003eIn conclusion, by comparing the ascending mucosal bacteria between post-cholecystectomy patients and healthy individuals, we reported mucosal bacterial dysbiosis in patients after cholecystectomy due to the alteration of flora composition based on Wilcoxon rank-sum test and LEfSe. Particularly, we found age notably affected the bacterial composition in PC patients. We subsequently noticed some specific bacteria have been changed between the groups, which may relate to colorectal cancer after cholecystectomy. Moreover, we used PICRUSTs to predict the metabolic pathways and discovered some of pathways remarkably changed in PC patients. Thus, our study provided a new insight into mechanism and therapeutics that could target the intestinal flora to attenuate related-diseases after cholecystectomy.\u003c/p\u003e\n\u003cp\u003eHowever, there exist some limitations in our study. First, the size of sample was not large enough. Second, it\u0026rsquo;s a retrospective and single-center research. Third, we only analyzed the differences of microbiota between patients with or without cholecystectomy, and no further analysis of causality as well as related mechanism. Additionally, we analyzed at the genus level, ignoring the discrepancy of different species among the same genus. Therefore, a prospective study in a larger scale is needed to find potential correlation between microbiota alteration and post-cholecystectomy syndrome, especially CRC. Future studies should use omics data to research intestinal microbiome, which may give more opportunities to expound the mechanism of increasing incidence of colon cancer after cholecystectomy.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the ethics committee of Shanghai General Hospital (approval No. 【2023】252). We certify that the study was performed in accordance with the 1964 declaration of HELSINKI and later amendments. Written informed consent was obtained from all subjects and/or their legal guardians prior to the enrollment of this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe 16S rRNA sequence data generated in this study have been deposited in the Sequence Read Archive database under accession number PRJNA938946. The URL is as follows: https://dataview.ncbi.nlm.nih.gov/object/PRJNA938946?reviewer=2d2mr5apu9st95am6n7jlf94r5. Now the data has been uploaded but not been public. The data will not be available until paper being accepted.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot Applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the Shanghai Natural Science Foundation Project (Grant No.22ZR1453500) and the fifth batch of medical key disciplines in Jiading District, Shanghai (2020‑jdyxzdxk‑15).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors claimed no conflicts of interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor\u0026rsquo;s contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors were involved in patients\u0026rsquo; enrollment, performing the study, acquisition of data and interpretation of study results. Miao-Yan Fan and You-Lu drafted the manuscript. Ying‑Ying Lu and Qiao-Li Jiang were involved in the study design and critical revision of the manuscript. All authors approved the final version of the manuscript, including the authorship list.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor details\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e1\u003c/sup\u003eShanghai Key Laboratory of Pancreatic Disease, Shanghai JiaoTong University School of Medicine, Shanghai, China\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e2\u003c/sup\u003eDepartment of Gastroenterology, Shanghai General Hospital, Shanghai JiaoTong University School of Medicine, Shanghai, China\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e3\u003c/sup\u003eDepartment of Gastroenterology, Jiading branch of Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003ePortincasa P, Di Ciaula A, de Bari O, Garruti G, Palmieri V, Wang D-H. 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Clin Infect Dis. 1999;28:476\u0026ndash;81.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYang L, Wu G, Wu Q, Peng L, Yuan L. METTL3 overexpression aggravates LPS-induced cellular inflammation in mouse intestinal epithelial cells and DSS-induced IBD in mice. Cell Death Discov. 2022;8:62.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLoke MF, Chua EG, Gan HM, Thulasi K, Wanyiri JW, Thevambiga I, et al. Metabolomics and 16S rRNA sequencing of human colorectal cancers and adjacent mucosa. PLoS ONE. 2018;13:e0208584.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"post-cholecystectomy, ascending colon mucosal, gut microbiota, colorectal cancer, diarrhea","lastPublishedDoi":"10.21203/rs.3.rs-3174409/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3174409/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eBACKGROUND\u003c/p\u003e\n\u003cp\u003eCholecystectomy is an effective therapy for gallstones, however, the incidence of CRC has increased significantly in post-cholecystectomy (PC) patients. Whether it is related to the changed mucosal microbiota in ascending colon is still unclear.\u003c/p\u003e\n\u003cp\u003eAIM\u003c/p\u003e\n\u003cp\u003eTo explore the association between gut microbiota and cholecystectomy.\u003c/p\u003e\n\u003cp\u003eMETHODS\u003c/p\u003e\n\u003cp\u003eMucosal biopsy samples were collected from 30 PC patients (the test group) with gallbladder stones and 28 healthy individuals (the control group) by colonoscopy. Subsequently, the test group was subdivided into the YMA group or SNR group(age over or under 60), DG group or NG group (with or without diarrhea) and Log group or Sht group(duration over or under 5 years) according to patients’ clinical characteristics. 16S-rRNA gene amplicon sequencing was performed and alpha diversity, beta diversity and composition analysis were determined. The Phylogenetic Investigation of Communities by Reconstruction of Unobserved States based on the Kyoto Encyclopedia of Genes and Genomes database was used to predict the function of the microbiome.\u003c/p\u003e\n\u003cp\u003eRESULTS\u003c/p\u003e\n\u003cp\u003eThe PC patients showed similar richness and overall composition with healthy controls, but PC patients over 60 years showed a different structure than those under 60 years. At the phylum level, the richness of \u003cem\u003eBacteroidetes\u003c/em\u003e was significantly higher in PC patients. Similarly, the genus \u003cem\u003eBacteroides\u003c/em\u003e, \u003cem\u003eParabacteroides\u003c/em\u003eand \u003cem\u003eBilophila \u003c/em\u003ewere remarkably more abundant in PC patients compared with the controls. In addition, the PC patients had significant enrichments in both metabolic pathways, including Lipopolysaccharide and vancomycin group antibiotics biosynthesis compared to the controls.\u003c/p\u003e\n\u003cp\u003eCONCLUSION\u003c/p\u003e\n\u003cp\u003eOur study suggested that mucosal microbiota was changed in PC patients, which may reveal new insight into therapeutic options for colorectal cancer and diarrhea after cholecystectomy.\u003c/p\u003e","manuscriptTitle":"Alteration of Ascending Colon Mucosal Microbiota in Patients after Cholecystectomy","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-08-08 14:41:33","doi":"10.21203/rs.3.rs-3174409/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"34c3c1d3-9b90-4335-b061-ca6cfd71e172","owner":[],"postedDate":"August 8th, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-03-05T06:47:04+00:00","versionOfRecord":[],"versionCreatedAt":"2023-08-08 14:41:33","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3174409","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3174409","identity":"rs-3174409","version":["v1"]},"buildId":"WrCJVZZCHTDjtuVLN7oU0","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}