Effect of intestinal microbiota on the recovery of bowel function for patients undergoing colon surgery: a prospective cohort study

Effect of intestinal microbiota on the recovery of bowel function for patients undergoing colon surgery: a prospective cohort study | 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 Effect of intestinal microbiota on the recovery of bowel function for patients undergoing colon surgery: a prospective cohort study Shuguang Yang, Yao Sun, Ting Wang, Huiying Zhao, Fengxue Zhu, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6637501/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 Purpose This study aimed to investigate the risk factors and gut microbiome characteristics influencing postoperative bowel functional recovery in patients undergoing colorectal surgery. Methods Patients who underwent colorectal surgery between January 2023 and October 2023 were stratified into two cohorts based on the timing of their first postoperative defecation (≤ 5 days vs. >5 days). Clinical data were systematically recorded, and identify independent risk factors associated with delayed bowel recovery. Fresh stool specimens were collected postoperatively and subjected to metagenomic sequencing to elucidate the relationship between gut microbiota composition and bowel functional outcomes. Results Thirty-five patients were enrolled in the study. Multivariate analysis identified time to first postoperative enteral feeding ( p < 0.01) as the independent risk factor for delayed defecation. Alpha diversity indices revealed no significant intergroup differences in microbial species richness. However, patients with prolonged postoperative defecation time (> 5 days) exhibited a reduced proportion of probiotic taxa (e.g., Bifidobacterium, Lactobacillus) and an elevated prevalence of pathogenic bacteria compared to the ≤ 5-day cohort. Metagenomic profiling further demonstrated impaired microbial metabolic pathways in the delayed recovery group, notably diminished carbohydrate metabolism (e.g., glycolysis/gluconeogenesis) and amino acid metabolism (e.g., selenocysteine and taurine biosynthesis). Conclusions Early postoperative resumption of enteral nutrition and probiotic may enhance bowel functional recovery. The observed reductions in microbial-driven gluconeogenesis/glycolysis, selenocysteine, and taurine synthesis suggest that dysregulation of these metabolic pathways may compromise intestinal mucosal repair and homeostasis, contributing to delayed postoperative recovery. Risk factor Intestinal microbiota Postoperative bowel function Colorectal surgery Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction The human intestine, harbouring approximately 3.8×10¹³ bacteria, constitutes a vast reservoir for microbial diversity[ 1 ]. Dysbiosis, characterised by the replacement of predominant obligate anaerobes with facultative anaerobes, promotes the proliferation of pathogenic microorganisms implicated in inflammatory bowel disease (IBD) and colorectal carcinogenesis[ 2 ]. Within the tumour microenvironment, innate immune cells secrete cytokines, chemokines, matrix metalloproteinases, growth factors, and reactive oxygen species, fostering DNA damage, unchecked cellular proliferation, and metastatic potential[ 3 ]. Emerging preclinical evidence underscores associations between gut microbiota/microecological perturbations and IBD pathogenesis, with IBD itself recognised as a predisposing factor for malignancy[ 4 ]. Colorectal cancer (CRC), the third most prevalent malignancy worldwide, accounts for 10% of global cancer diagnoses and 9.4% of cancer-related mortality, ranking as the second leading cause of oncological death[ 5 ]. While surgical resection remains the therapeutic cornerstone for CRC, postoperative bowel functional recovery is influenced by multifactorial determinants. Contemporary national and international studies on post-anaesthetic intestinal rehabilitation highlight key modulators, including minimally invasive surgical techniques, early enteral nutrition, and targeted probiotic supplementation[ 6 – 8 ]. The adoption of Enhanced Recovery After Surgery (ERAS) protocols has further optimised postoperative bowel recovery in CRC patients[ 9 ]. Nevertheless, perioperative interventions—such as mechanical bowel preparation, prophylactic antibiotic regimens, surgical trauma, and perioperative fluid management—induce microbiota perturbations correlated with postoperative complications, including anastomotic leakage and surgical site infections[ 10 ]. Consequently, elucidating the interplay between gut microbiota dynamics and bowel functional outcomes in colorectal surgical patients represents a critical research imperative. Methods Study design and ethics A prospective study was conducted to investigate the role and impact of intestinal microbiota in recovery of bowel function for patients undergoing colon surgery. This study was approved by the Ethics committee of Peking University People’s Hospital (2022PHB053-001, Beijing, China). All patients provided written informed consent before participating in the study. Participants Adult patients undergoing colorectal surgery at Peking University People’s Hospital between January 1st, 2023 and October 31th 2023 were eligible for inclusion. All patients were treated with oral laxatives for bowel preparation. The general anesthesia of all participants were intravenous propofol, remifentanil, and dexmedetomidine combined with inhalation of sevoflurane. All participants underwent preoperative bowel preparation with oral laxatives. General anaesthesia was administered using intravenous propofol, remifentanil, and dexmedetomidine in combination with inhaled sevoflurane. Perioperative infection prophylaxis comprised cefoperazone-sulbactam, while postoperative analgesia was achieved via opioid and non-steroidal anti-inflammatory drug regimens. Excluded criteria were defined as fellows: Patients who had a history of surgical reconstruction of the gastrointestinal tract. Patients who have used probiotics within the preceding 3 months. Patients who were younger than 18 years. Patients who withdrawal or refusal to participate. Clinical data records were incomplete. Previous studies report a mean first postoperative defecation time of 5 days in colorectal surgery patients [ 11 ]. In this study, participants were stratified into two cohorts: Group A (first postoperative defecation ≤ 5 days) and Group B (first postoperative defecation > 5 days). Data collection Patient’s demographic variables—including age, sex, and body mass index (BMI)—were systematically recorded. Pre-existing comorbidities (e.g., hypertension, coronary heart disease [CHD], arrhythmia, cerebral infarction, intracranial haemorrhage, hypothyroidism, diabetes mellitus, chronic obstructive pulmonary disease [COPD], renal insufficiency, hyperlipidaemia, hepatic insufficiency, and haematological disorders) diagnosed prior to admission were documented in a case report form (CRF) Excel database. Data of preoperative chemotherapy, preoperative anemia, preoperative ileus, the American Society of Anesthesiologists (ASA) classification, bowel preparation before surgery (soapsuds enema, oral laxatives, glycerin enema, and oral antibiotics) were adopted in CRF. Data of surgery such as surgical site (right hemicolectomy, transverse colectomy, left hemicolectomy, sigmoid colectomy, and proc tectomy), surgical approach (laparotomy or laparoscopic surgery), duration of operation, and intraoperative bleeding were entered into CRF. Postoperative data including time of the first postoperative feeding (day), duration of analgesia and antibiotics, and hypoproteinemia were entered recorded. All data were obtained by medical record such as papery medical records library or electronic medical record system. Stool sample collection Fresh stool sample (not less 6 gram) were collected from participants and immediately stored at -80℃ at the time of the first postoperative defecation. Materials and Methods for Metagenomics DNA extractions DNA was extracted using the E.Z.N.A.® Stool DNA Kit (D4015-02, Omega, Inc., USA) in accordance with the manufacturer’s guidelines. The reagent effectively isolates bacterial DNA from trace samples. Negative controls (unused swabs processed identically) confirmed no DNA contamination. Eluted DNA (50 µl) was stored at − 80°C prior to PCR analysis (LC-BIO, TECHNOLOGIES (HANGZHOU) CO., LTD., Hangzhou, Zhejiang Province, China), following a modified QIAGEN protocol. DNA Library Construction Libraries were constructed with the TruSeq Nano Kit (Illumina). DNA fragmentation used dsDNA Fragmentase (NEB) at 37°C/30 min. Blunt-end fragments were generated, size-selected with purification beads, and A-tailed for adapter ligation. Indexed adapters (T-overhang) enabled single/paired-end sequencing. PCR amplification conditions: 95°C/3 min; 8 cycles (98°C/15 s, 60°C/15 s, 72°C/30 s); 72°C/5 min. Data analysis Raw sequencing data were processed through adapter removal (Cutadapt), quality trimming (Fqtrim), and host DNA filtering (Bowtie2), followed by de novo metagenome assembly (IDBA-UD). Coding sequences were predicted (MetaGeneMark), clustered into unigenes (CD-HIT), and quantified as TPM. Taxonomic classification (DIAMOND vs NCBI NR) and functional annotation (GO/KEGG/eggNOG/CAZy/CARD/PHI/MGEs/VFDB) were performed, with differential analysis (Fisher’s exact/Kruskal-Wallis tests) applied to taxonomic, functional, and gene-level features (Fig. 1 ). Statistical analysis Univariate analysis was conducted using SPSS 26.0 software (IBM, Armonk, NY, USA) to identify potential risk factors influencing the timing of first postoperative defecation. Normally distributed quantitative data were expressed as mean ± standard deviation (SD), while non-normally distributed variables were reported as medians and interquartile ranges (IQR), with between-group comparisons performed via one-way analysis of variance (ANOVA). Categorical variables were summarised as frequencies and percentages. For categorical data, statistical descriptions employed frequency and proportional composition, with intergroup comparisons assessed using the χ² test or Fisher’s exact test, as appropriate. Variables achieving statistical significance ( p < 0.05) in univariate analysis were entered into a multivariate logistic regression model employing backward stepwise elimination to identify independent predictors of delayed postoperative defecation. Odds ratios (OR) and corresponding 95% confidence intervals (CI) were calculated to quantify associations. A two-tailed p -value < 0.05 was deemed statistically significant for all analyses. Results Baseline characteristics between January 1st, 2023 to October 31th 2023, 93 patients were assessed for eligibility, with 35 participants ultimately enrolled following exclusions (Fig. 2 ). Seven participants experienced a first postoperative defecation time exceeding 5 days. he cohort had a mean age of 62.49 ± 11.74 years (ranged: 35–87 years), with baseline clinical characteristics summarised in Table 1 . Transverse colectomy ( p = 0.04), malignancy( p = 0.04), operative duration ( p = 0.01), and time of postoperative feeding( p < 0.01) demonstrated statistically difference between groups in patients undergoing colorectal surgery. Table 1 Baseline and characteristics of postoperative defection for patients undergoing colon surgery variables GroupA(≤ 5day) n = 28 GroupB(> 5day) n = 7 χ 2 / t P value Female 15(53.6%) 3(42.9%) 0.26 0.61 Age(years) 61.43 ± 12.47 66.71 ± 7.39 1.26 0.29 BMI a (kg/m 2 ) 24.34 ± 3.99 23.21 ± 3.02 0.92 0.18 ASA b classification 1.64 0.44 Ⅰ 1(3.6%) 0 Ⅱ 24(85.7) 5(71.4%) Ⅲ 3(10.7%) 2(28.6%) Probiotics 8(28.6%) 2(28.6%) 0 1.00 Right colectomy 13(46.4%) 2(28.6%) 0.73 0.39 Transverse colectomy 1(3.6%) 2(28.6%) 4.47 0.04 Left colectomy 2(7.1%) 0 5.3 0.47 Sigmoid colectomy 13(46.4%) 3(42.9%) 0.29 0.87 Preoperative ileus 5(17.9%) 1(14.3%) 0.05 0.82 Hypertension 6(21.4%) 2(28.6%) 0.16 0.69 CHD c 2(7.1%) 0 0.53 0.47 Diabetes mellitus 7(25.0%) 1(14.3%) 0.37 0.55 COPD d 1(3.6%) 1(14.3%) 1.19 0.28 Malignancy 28(100%) 6(85.7%) 4.12 0.04 Laparotomy 4(14.3%) 2(28.6%) 0.81 0.37 Duration of operative (min) 158.04 ± 49.30 215.00 ± 39.37 0.1 0.01 Intraoperative bleeding 53.93 ± 38.43 94.26 ± 135.26 9.31 0.18 Time of postoperative feeding(day) 3.36 ± 0.83 5.86 ± 1.68 5.69 < 0.01 Duration of analgesia 3.04 ± 0.43 3.29 ± 0.95 7.53 0.30 Duration of antibiotics 25(89.3%) 7(100%) 0.82 0.37 Hypoproteinemia 10(35.7%) 3(42.9%) 0.12 0.73 a BMI: Body mass index, b ASA American society of Aneshesiologists, cCHD: Coronary atherosclerotic heart disease, d COPD: Chronic obstructive pulmonary disease Primary outcome. Multivariate analysis identified time to postoperative feeding as the sole independent risk factor for delayed defecation (19.53, 95%CI [1.80, 211.60]. p = 0.01). Microbiome analysis MetaGeneMark software(v3.38) was employed to predict the CDS and assess biodiversity for contigs (≥ 500 bp) assembled per sample. Sequences with CDS lengths < 100 nucleotides (nt) were filtered based on prediction outcomes. Subsequent clustering was performed at 95% sequence identity and 90% coverage, with the longest sequence selected as the representative to construct the Unigenes set. Comparative analysis revealed fewer Unigenes in patients with first postoperative defecation time > 5 days versus those with ≤ 5 days, evident in both nucleic acid and protein sequence predictions (Additional file figure S1 ). Species richness and community evenness were quantified using Chao1, Observed species, Shannon, and Simpson indices (Table 2 ). Rarefaction curve analysis, simulating resampling processes to estimate environmental species richness, demonstrated no statistically significant differences in alpha diversity indices between the ≤ 5-day and > 5-day cohorts (Fig. 3 ). Table 2 Analysis of Alpha diversity index of intestinal microbiome for patients undergoing colon surgery GroupA(≤ 5day) GroupB(> 5day) P value Chao1 2482.90 ± 804.45 2552.80 ± 1021.13 0.65 Observed_species 1914.60 ± 662.93 1985.50 ± 795.87 0.68 Shannon 4.88 ± 1.02 4.86 ± 0.90 0.96 Simpson 0.88 ± 0.07 0.89 ± 0.09 0.84 Microbiome composition Unigenes protein sequences were aligned against the NR_meta library (a microbial-specific subset of the NCBI NR database comprising 52,375,954 sequences) using DIAMOND software (blastp; e-value ≤ 1×10⁻⁵). Species classification was assigned based on the highest-scoring match for each Unigene. Taxonomic abundance was calculated at each hierarchical level, with the top 20 most abundant species retained for visualisation; remaining taxa were aggregated as "Others". Species richness analysis Comparative taxonomic profiling revealed a lower proportion of probiotic taxa (e.g., Lactobacillus, Bifidobacterium) and elevated pathogenic bacteria in patients with prolonged postoperative defecation (> 5 days) versus the ≤ 5-day cohort. The ≤ 5-day group exhibited higher proportions of Bacteroidetes and Archaea, but reduced Proteobacteria, Firmicutes, Actinobacteriota, and Chytridiomycota in Phylum level (Additional file figure S2). Dominant taxa included Bacteroidia, Proteobacteria, Clostridia, Bacilli, Actinobacteria, and β-proteobacteria. The > 5-day cohort demonstrated increased Bacteroidia and α-proteobacteria, but diminished Proteobacteria, Bacilli, and Actinobacteria in Class level (Additional file Figure S3). Significant reductions in Lactobacillales and Enterobacterales were observed in the > 5-day group in Oder level (Additional file Figure S4). At the classification of Family, The > 5-day cohort showed reduced Enterobacteriaceae, Enterococcaceae, and Coriobacteriaceae, but elevated Klebsiellaceae and Mucoraceae (Additional file Figure S5). Depleted Enterococcus, Escherichia, Ruminococcus, and Bifidobacterium contrasted with enriched Klebsiella in the > 5-day group in Genus Level (Additional file Figure S6). At the species level, Probiotic taxa (Escherichia coli, Enterococcus faecalis, Bacteroides multivorans, Bifidobacterium spp., Clostridium prasicolum) were reduced, while pathogens (Bacteroides fragilis, Klebsiella pneumoniae, Bacteroides faecalis) predominated in delayed recovery patients (Additional file Figure S7). Analysis of species richness differences Using thresholds of |logFC| >1 and p < 0.05, Proteobacteria, Firmicutes, Actinobacteria, Bacteroidetes, and viral taxa exhibited the greatest intergroup abundance disparities (Additional file Figure S8). It was found that the species abundance of Ruminococcus ( p < 0.01), Lachnospiraceae( p < 0.01), Escherichia_albertii( p < 0.01), and Escherichia_sp._4_140B( p < 0.01) was lower in 5-day cohort. While the species abundance of Ruminococcaceae ( p < 0.01), Subdoligranulum ( p < 0.01), Bacteroidetes ( p < 0.01), Ruminococcaceae_bacterium ( p < 0.01) was higher in 5-day cohort (Fig. 4 A). The contribution of the difference in species abundance for the time of postoperative defecation prolonged was obtained through the Random Forest algorithm. Gini Index analysis identified Alistipes AF48.12, Clostridium sp. AF12.41, Hyphomicrobiaceae bacterium, Paenibacillus sp. PY1325, Bacteroides spp., and Yersinia enterocolitica as key contributors to delayed postoperative defecation (Fig. 4 B). Functional annotation of intestinal microbiome metabolism I The top 30 GO terms with the smallest p -values were selected from the Gene Ontology Consortium database to compare functional annotations of Unigene protein sequences between groups (Additional file Figure S9). Comparative analysis revealed significant reductions in Group B (> 5-day cohort) for the following processes: peptidase activity( p < 0.01), DNA replication initiation( p < 0.01), pyrimidine nucleobase metabolic process( p < 0.01), phosphate acetyltransferase activity( p < 0.01), glutamate biosynthetic process( p < 0.01), pyrimidine nucleoside salvage( p < 0.01), and enzyme-directed rRNA2’-O-methylation( p 5-day cohort. Key impaired pathways included: biosynthesis of secondary metabolites, microbial metabolism in diverse environments, cofactor biosynthesis, amino acids biosynthesis, two-component regulatory systems, ABC transporters, carbon metabolism, ribosomal function, purine metabolism, amino sugar and nucleotide sugar metabolism, quorum sensing, glycolysis/gluconeogenesis, starch and sucrose metabolism, pyruvate metabolism, pyrimidine metabolism, and galactomyces Sugar metabolism, cysteine and methionine metabolism, fructose and mannose metabolism, and oxidative phosphorylation in the group of patients with the time of first postoperative defecation > 5days(Additional file Figure S10). At the KEGG Pathway Definition level, further analysis identified reduced activity in: Fiagellar assembly( p < 0.01), Glycolysis/Gluconeogenesis( p < 0.01), D-glutamine and D-glutamate metabolism ( p < 0.01), Cysteine and methiomine metabolism( p < 0.01), selenocompound metabolism( p < 0.01), Aminoacyl-tRNA biosynthesis( p < 0.01), protein export( p < 0.01), Peptidoglycan biosynthesis( p < 0.01), D-Alanine metabolism( p < 0.01), and pyrimidine metabolism( p < 0.01) (Fig. 5 B). Discussion In this study, metagenomic sequencing was performed on fecal specimens from the first postoperative defecation of patients after colon surgery to analyze gut microbiota composition, predominantly comprising Bacteroidetes, Proteobacteria, Firmicutes, and Actinobacteria. Patients with prolonged postoperative defecation time exhibited a reduced proportion of probiotic taxa and an elevated prevalence of pathogenic bacteria. However, no statistically significant intergroup differences in gut biodiversity were observed postoperatively. Functional annotation and comparative analysis of Unigene protein sequences across multiple databases revealed that delayed defecation was associated with impaired intestinal digestion/absorption capacity, diminished mucosal barrier integrity, and reduced epithelial repair mechanisms. Studies investigating the gut microbiota-colorectal cancer axis have confirmed reduced microbial diversity in colorectal cancer patients. Research on postoperative anastomotic leakage further demonstrated that patients without leakage exhibited higher gut microbial diversity, whereas leakage correlated with diminished diversity and elevated Bacteroidaceae and Lachnospiraceae (notably Blautia) abundance [ 12 ]. In this cohort, prolonged postoperative defecation time similarly corresponded to reduced microbial diversity. However, non-parametric intergroup comparisons of biodiversity indices lacked statistical significance, potentially attributable to the limited sample size of the > 5-day cohort (n = 7). The widespread implementation of Enhanced Recovery After Surgery (ERAS) protocols and standardised perioperative care has shortened postoperative recovery milestones, including time to first flatus and defecation. An alternative explanation is that, despite delayed defecation, partial restoration of microbiota diversity and metabolic functions may commence during bowel movement recovery, potentially obscuring statistically significant correlations between microbial diversity and defecation timing in this analysis. The gut microbiota of healthy individuals is typically dominated by one archaeal phylum and five bacterial phyla: Bacteroidetes, Firmicutes, Actinobacteria, Proteobacteria, and Verrucomicrobia. Diets rich in sugar and animal fat but low in fibre correlate with elevated Bacteroidetes abundance, whereas high-fibre diets favour Firmicutes proliferation[ 13 ]. In colorectal cancer (CRC), specific pathogens such as Fusobacterium nucleatum, Escherichia coli, Bacteroides fragilis, and Campylobacter jejuni drive tumourigenesis by fostering a pro-oncogenic microenvironment[ 14 ]. Bacteroides fragilis, a common gut symbiont critical for digestion and mucosal health, exists as two subtypes: non-toxigenic B. fragilis and enterotoxigenic B. fragilis (ETBF). ETBF secretes B. fragilis toxin (BFT), which disrupts epithelial integrity via E-cadherin cleavage, activates Wnt/β-catenin signalling, induces chronic inflammation, and promotes carcinogenesis. ETBF further upregulates spermine oxidase in colonocytes, amplifying reactive oxygen species (ROS) production, DNA damage, and CRC progression[ 15 ]. In this study, gut microbiota abundance was compared across six taxonomic levels (Phylum to Species) between patients with postoperative defecation times ≤ 5 days (> 5-day cohort). Key findings included: elevated pathogens were Bacteroides fragilis, Ruminococcus spp., and Klebsiella pneumoniae in the > 5-day cohort. Depleted beneficial taxa were Enterococcus faecalis, Bifidobacterium spp., and Bacteroides thetaiotaomicron in delayed recovery patients. Ruminococcus (Gram-positive anaerobe; Lachnospiraceae family) degrades cellulose and carbohydrates, producing acetate and formate. While historically linked to Crohn’s disease and irritable bowel syndrome via butyrate metabolism[ 16 ], its paradoxical abundance in the ≤ 5-day cohort—despite reduced carbohydrate metabolism in delayed patients—suggests strain-specific functional heterogeneity warranting further investigation. Bacteroides is one of the dominant anaerobic geuns in the human gut. Its main function is to degrade large-molecule carbohydrates in plant foods into glucose and other easily digestible small-molecule sugars. acteroides, a dominant anaerobic genus, hydrolyses complex plant polysaccharides into absorbable sugars. Bacteroides thetaiotaomicron, encoding glycoside hydrolases and modulating glutamate metabolism, is pivotal for ileal/colonic mucosal health. Its depletion in the > 5-day cohort may impair carbohydrate processing and epithelial repair [ 17 ]. Bifidobacterium and Lactobacillus (common probiotics) inhibit harmful bacteria, enhance gut barrier integrity, and suppress pro-inflammatory cytokines Reduced Bifidobacterium and Lactobacillus (immunomodulatory probiotics) likely compromised gut barrier integrity and anti-inflammatory capacity [ 18 ]. Similarly, diminished Enterococcus faecalis(a Gram-positive facultative anaerobe used in dysbiosis therapy) may reflect impaired microbial resilience [ 19 ]. It is well-established that gut microbiota predominantly interact with intestinal epithelial and stromal cells to maintain microenvironmental homeostasis. For instance, Bifidobacterium and Lactobacillus ferment fructooligosaccharides to produce lactate and acetate, which are subsequently metabolised by commensals such as Faecalibacterium into butyrate[ 20 ]. Butyrate serves as the principal energy substrate for colonic enterocytes. It enhances epithelial integrity by upregulating MUC2 (encoding mucin 2) and modulating tight junction protein expression, thereby fortifying the intestinal barrier. Additionally, butyrate lowers luminal pH, sustains microbial equilibrium, activates AMP-activated protein kinase (AMPK) to stimulate enterocyte differentiation, and reinforces mucosal defence mechanisms[ 21 ]. Beyond its metabolic roles, butyrate exhibits anti-inflammatory and anti-neoplastic properties through direct modulation of colonic cell metabolism and mucosal immunity[ 22 ]. Functional annotation of differentially expressed genes in this study revealed diminished carbohydrate metabolism in patients with delayed postoperative bowel recovery. This impairment likely stems from probiotic depletion, resulting in compromised dietary fibre processing, epithelial barrier dysfunction, and prolonged intestinal hypomotility. Dietary fibre degradation—mediated by symbiotic bacteria such as Bacteroides via glycan-sensing enzymes—generates short-chain fatty acids (SCFAs). SCFAs bind G protein-coupled receptors, inducing tolerogenic dendritic cell phenotypes, promoting regulatory T-cell (Treg) differentiation, polarising macrophages towards an M2 anti-inflammatory state, and stabilising gut homeostasis[ 23 ]. In this cohort, reduced glycolysis/gluconeogenesis and fructose/mannose metabolism in delayed recovery patients correlated with attenuated immunomodulatory capacity in intestinal epithelia. Probiotics enhance bile salt hydrolase (BSH) activity, catalysing taurine dissociation from tauro-conjugated bile acids[ 24 ]. I The observed taurine metabolism deficit in delayed recovery patients may reflect probiotic insufficiency. Selenium, an essential trace element incorporated as selenocysteine (the 21st proteogenic amino acid), is critical for intestinal redox homeostasis. Selenoproteins—including glutathione peroxidase, selenoprotein S, and selenoprotein P—orchestrate antioxidant defences, mitigate oxidative stress, and suppress chronic inflammation[ 25 ]. Preclinical evidence indicates gut microbiota composition modulates host selenium bioavailability, influencing selenoprotein expression and inflammatory responses[ 26 ]. The reduced selenocysteine incorporation observed in this study suggests impaired mucosal protection mechanisms in delayed recovery patients. This study investigated the role of gut microbiota in postoperative intestinal recovery following colorectal surgery through metagenomic sequencing of faecal samples obtained during the first postoperative bowel movement. Key limitations include: (1) Sample Size Constraints: ① Rapid hospital discharge protocols, increasingly prevalent in recent years, have reduced inpatient stays to ≤ 7 days, complicating the collection of preoperative, intraoperative, and immediate postoperative faecal specimens. ② Suboptimal patient adherence—particularly delayed reporting of bowel movements—frequently precluded timely sample acquisition. ③ The prohibitive cost of metagenomic sequencing restricted cohort expansion (2) Mechanistic Ambiguities: Despite advancements in 16S rRNA and next-generation sequencing (NGS) technologies, which have catalysed discoveries in microbial diversity and host-microbe interactions, the precise mechanisms underpinning gut microbiota’s influence on intestinal function remain incompletely resolved. The gut microbiome encompasses a vast array of species with pleiotropic roles, ranging from direct mucosal crosstalk to systemic effects mediated via inflammatory cytokines and microbial metabolites. While implicated in pathologies such as chronic inflammation, oncogenesis, neuropsychiatric disorders, and metabolic diseases, current evidence remains insufficient to delineate causal pathways or molecular mediators. These gaps underscore the necessity for hypothesis-driven studies integrating multi-omics approaches (e.g., metabolomics, transcriptomics) to unravel microbiota-host dynamics in postoperative recovery. Conclusion Timely resumption of enteral nutrition facilitates the restoration of postoperative bowel motility in patients undergoing colorectal surgery. A reduced proportion of probiotics and an increased abundance of pathogenic bacteria may delay the time of postoperative defecation for patients undergoing colon surgery. The reduction of metabolism in the bowel flora, namely the decrease of butyrate, taurine and selenocysteine, may prolong the recovery of postoperative bowel function for patients undergoing colon surgery. Abbreviations IBD Inflammatory bowel disease, CRC:Colorectal cancer, ERAS:Enhanced recovery after surgery, BMI:Body mass index CHD Coronary heart disease COPD Chronic obstructive pulmonary disease ASA American Society of Anesthesiologists NSAIDs Non-steroidal anti-inflammatory drugs CRF case report form CDS Coding regions, SD:Standard deviations, OR:Odds ratios CI Confidence intervals GO Gene Ontology Consortium, KEGG:Kyoto Encyclopedia of Genes and Genomes, ETBF:Enterotoxigenic B. fragilis, ROS:Reactive oxygen species, MUC2:Mucin 2, Oligomeric Mucus/Gel-Forming, AMPK:Adenosine 5‘-monophosphate-activated protein kinase, SCFAs:Short-chain fatty acids, BSH:Bile salt hydrolase. Declarations Author contributions SY and ZG designed the study. SY and YS participated in the literature search, analysis of data, as well as manuscript writing. YY participated in the literature search and data analysis and YA revised the manuscript. HZ and ZF participated in the data analysis and revised the manuscript. HZ had made contributions to the acquisition, analysis of data. SY and YS are equal the first author. YY and ZG are corresponding authors and are responsible for ensuring that all listed authors have approved the manuscript before submission. All authors approved the final manuscript for publication. Funding This work was supported by National Nature Science Foundation of China (grant number 92478117). Data availability statement The data are available from the corresponding author on reasonable request. But the datasets are not are not publicly available due to privacy or ethical restrictions. Ethics approval and consent to participate This study was approved by medical ethics committee of Peking University People’s Hospital(2022PHB053-001). Conformed with the provisions of the Declaration of Helsinki. Written, informed consent was obtained from all patients Consent publication Not applicable. Competing interests The authors declared no potential conflict of interest concerning the research, authorship, and/or publication of this article. Acknowledgements Thank you for all participants for accomplishing this study. References Sender R, Fuchs S, Milo R: Are We Really Vastly Outnumbered? Revisiting the Ratio of Bacterial to Host Cells in Humans . Cell 2016, 164 (3):337-340. Irrazábal T, Belcheva A, Girardin SE, Martin A, Philpott DJ: The multifaceted role of the intestinal microbiota in colon cancer . Molecular cell 2014, 54 (2):309-320. Coussens LM, Werb Z: Inflammation and cancer . Nature 2002, 420 (6917):860-867. 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Gut microbes 2021, 13 (1):1-20. Xue L, He J, Gao N, Lu X, Li M, Wu X, Liu Z, Jin Y, Liu J, Xu J et al : Probiotics may delay the progression of nonalcoholic fatty liver disease by restoring the gut microbiota structure and improving intestinal endotoxemia . Scientific reports 2017, 7 :45176. Krawczyk B, Wityk P, Gałęcka M, Michalik M: The Many Faces of Enterococcus spp.-Commensal, Probiotic and Opportunistic Pathogen . Microorganisms 2021, 9 (9). Krumbeck JA, Rasmussen HE, Hutkins RW, Clarke J, Shawron K, Keshavarzian A, Walter J: Probiotic Bifidobacterium strains and galactooligosaccharides improve intestinal barrier function in obese adults but show no synergism when used together as synbiotics . Microbiome 2018, 6 (1):121. Ma X, Fan PX, Li LS, Qiao SY, Zhang GL, Li DF: Butyrate promotes the recovering of intestinal wound healing through its positive effect on the tight junctions . Journal of animal science 2012, 90 Suppl 4 :266-268. van der Beek CM, Dejong CHC, Troost FJ, Masclee AAM, Lenaerts K: Role of short-chain fatty acids in colonic inflammation, carcinogenesis, and mucosal protection and healing . Nutrition reviews 2017, 75 (4):286-305. Moffa S, Mezza T, Cefalo CMA, Cinti F, Impronta F, Sorice GP, Santoro A, Di Giuseppe G, Pontecorvi A, Giaccari A: The Interplay between Immune System and Microbiota in Diabetes . Mediators of inflammation 2019, 2019 :9367404. Ahmadi S, Wang S, Nagpal R, Wang B, Jain S, Razazan A, Mishra SP, Zhu X, Wang Z, Kavanagh K et al : A human-origin probiotic cocktail ameliorates aging-related leaky gut and inflammation via modulating the microbiota/taurine/tight junction axis . JCI insight 2020, 5 (9). Reeves MA, Hoffmann PR: The human selenoproteome: recent insights into functions and regulation . Cellular and molecular life sciences : CMLS 2009, 66 (15):2457-2478. Ivanov, II, Honda K: Intestinal commensal microbes as immune modulators . Cell host & microbe 2012, 12 (4):496-508. Additional Declarations No competing interests reported. Supplementary Files Additionalfile.docx 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-6637501","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":468101305,"identity":"981d8a75-3e0f-4fcb-841a-cf0a1b2c0ce1","order_by":0,"name":"Shuguang Yang","email":"","orcid":"","institution":"Peking University People’s Hospital","correspondingAuthor":false,"prefix":"","firstName":"Shuguang","middleName":"","lastName":"Yang","suffix":""},{"id":468101306,"identity":"ade46cf3-cfa1-4c5a-af6e-4d2f74c7f992","order_by":1,"name":"Yao Sun","email":"","orcid":"","institution":"Peking University People’s Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yao","middleName":"","lastName":"Sun","suffix":""},{"id":468101307,"identity":"d20c0619-21e6-4258-b6d9-55ac216ee86a","order_by":2,"name":"Ting Wang","email":"","orcid":"","institution":"Peking University People’s Hospital","correspondingAuthor":false,"prefix":"","firstName":"Ting","middleName":"","lastName":"Wang","suffix":""},{"id":468101308,"identity":"3a420646-269a-4ed5-81d1-6ed3c4254685","order_by":3,"name":"Huiying Zhao","email":"","orcid":"","institution":"Peking University People’s Hospital","correspondingAuthor":false,"prefix":"","firstName":"Huiying","middleName":"","lastName":"Zhao","suffix":""},{"id":468101309,"identity":"631791ef-af60-48dc-b530-0bf6a9868cae","order_by":4,"name":"Fengxue Zhu","email":"","orcid":"","institution":"Peking University People’s Hospital","correspondingAuthor":false,"prefix":"","firstName":"Fengxue","middleName":"","lastName":"Zhu","suffix":""},{"id":468101310,"identity":"f4c8acb4-4a08-4578-a8c8-a5f96272a337","order_by":5,"name":"Youzhong An","email":"","orcid":"","institution":"Peking University People’s Hospital","correspondingAuthor":false,"prefix":"","firstName":"Youzhong","middleName":"","lastName":"An","suffix":""},{"id":468101311,"identity":"3aa28d9a-23f1-464e-927c-aa983f2fb2b7","order_by":6,"name":"Hua Zhang","email":"","orcid":"","institution":"Peking University Third Hospital","correspondingAuthor":false,"prefix":"","firstName":"Hua","middleName":"","lastName":"Zhang","suffix":""},{"id":468101312,"identity":"42376587-893b-40f2-88da-e94d712ddcde","order_by":7,"name":"Zhidong Gao","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+0lEQVRIiWNgGAWjYJACZgYDZhB18EGCgQ0PP38D0VrYkg0+VKTJSM44QIwWEGLgUROcceawjUFDAn7l8u6HD38uKLCWM+dfw8bM23aex4DhAOOHjzm4tRieSUswnmGQbmw54+2xx7xtt3nMmRuYJWduw6OlIccgmcfgcOKGG+fSjUFaLBsOAK3Dp6X/jcFhiJYzZtK8bed4DA4k4NciL5Fj2AzWcr7HTHLGmQOEtRhIPEtm5gH6xeAGOJCTeSRnHGzG6xf5/uTDn3n+WMsZnD8Miko7e37+5oMfPuKz5QCMJZEAYzE24FYPsgUuzX8At6pRMApGwSgY2QAA+JVVxD7G1cUAAAAASUVORK5CYII=","orcid":"","institution":"Peking University People’s Hospital","correspondingAuthor":true,"prefix":"","firstName":"Zhidong","middleName":"","lastName":"Gao","suffix":""},{"id":468101313,"identity":"6ebf5d96-7e40-4747-8765-1d60243db26c","order_by":8,"name":"Yingjiang Ye","email":"","orcid":"","institution":"Peking University People’s Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yingjiang","middleName":"","lastName":"Ye","suffix":""}],"badges":[],"createdAt":"2025-05-11 04:08:07","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6637501/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6637501/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":84328473,"identity":"39b59948-f281-4355-9ad6-3e1f329ca54b","added_by":"auto","created_at":"2025-06-10 15:38:13","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":734257,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFlowchart for metagenomic detection of bowel flora\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6637501/v1/bcd151bc7e0f29cf057cc930.jpg"},{"id":84328477,"identity":"0ec013e7-beb5-45d7-991b-154839a035dd","added_by":"auto","created_at":"2025-06-10 15:38:13","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":443754,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFlowchart of participants enrolled in this study\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6637501/v1/543f1d76c756b24182464621.jpg"},{"id":84330711,"identity":"50c082e1-ade4-4a55-9309-2bb762381c5f","added_by":"auto","created_at":"2025-06-10 15:54:14","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":67064,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eBox plot of postoperative bowel flora diversity for patients undergoing colon surgery. The left side of the graph shows different diversity indices, and the upper left corner shows the \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003ep\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003evalue. A: Postoperative defecation time ≤5 days, B: Postoperative defecation time \u0026gt;5 days\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Figure3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6637501/v1/799c2be543155c24a0892d0f.jpg"},{"id":84329692,"identity":"5b5a0d36-bf7c-4079-bad2-da958a1a9ec5","added_by":"auto","created_at":"2025-06-10 15:46:14","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":109763,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDifferences of Species richness between two groups, A: Box plot of species differences in bowel flora for patients undergoing colon surgery (Species). B: Random forest plot of the difference in bowel species abundance for patients undergoing colon surgery. Different colors represent different species. The closer the color is to red, the smaller the \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003ep\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e value. The larger the Gini Index, the greater the importance of the species. A: Postoperative defecation time ≤5 days, B: Postoperative defecation time \u0026gt;5 days.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Figure4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6637501/v1/b5eadc3e9a7757b78dbf3045.jpg"},{"id":84328490,"identity":"c6aaf716-8663-4188-be12-3ed33da276fc","added_by":"auto","created_at":"2025-06-10 15:38:14","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":100866,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ethe differential GO and KEGG enrichment map of bowel Unigene for patients undergoing colon surgery. A: The differential GO enrichment map. Genes in GO to the total number of genes in GO (Rich Factor). The larger the Rich Factor, the higher the enrichment degree of GO. The vertical coordinate represents the functional annotation of GO, the number of Unigene groups that meet the difference in bubble size. B: Enrichment map of the differential KEGG pathway of Unigene in the bowel of patients undergoing colon surgery. the horizontal coordinate Rich Factor represents the ratio of the number of differential Unigene genes located in the KEGG database pathway to the total number of genes in this pathway. The larger the Rich Factor, the higher the degree of pathway enrichment. The vertical coordinate is the KEGG path; The size of the bubble represents the number of Unigene differences. The color of the bubble represents the \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003ep\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e-value of the enrichment analysis. The closer the bubble color is to red, the smaller the \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003ep\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e-value.\u003c/strong\u003e \u003cstrong\u003eA: Postoperative defecation time ≤5 days, B: Postoperative defecation time \u0026gt;5 days.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Figure5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6637501/v1/79a81ec7e783b27338891166.jpg"},{"id":86640545,"identity":"8f3dd997-4886-4bca-9914-ba9569c8fdf6","added_by":"auto","created_at":"2025-07-14 08:09:16","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4109251,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6637501/v1/b02dbfb1-1581-45ba-addb-590f86912942.pdf"},{"id":84328475,"identity":"97ccdbfa-3587-4b4f-b3c0-d80407a73d6a","added_by":"auto","created_at":"2025-06-10 15:38:13","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":3483794,"visible":true,"origin":"","legend":"","description":"","filename":"Additionalfile.docx","url":"https://assets-eu.researchsquare.com/files/rs-6637501/v1/37798e4b82d52dbc1fd10cdc.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Effect of intestinal microbiota on the recovery of bowel function for patients undergoing colon surgery: a prospective cohort study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe human intestine, harbouring approximately 3.8\u0026times;10\u0026sup1;\u0026sup3; bacteria, constitutes a vast reservoir for microbial diversity[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Dysbiosis, characterised by the replacement of predominant obligate anaerobes with facultative anaerobes, promotes the proliferation of pathogenic microorganisms implicated in inflammatory bowel disease (IBD) and colorectal carcinogenesis[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Within the tumour microenvironment, innate immune cells secrete cytokines, chemokines, matrix metalloproteinases, growth factors, and reactive oxygen species, fostering DNA damage, unchecked cellular proliferation, and metastatic potential[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Emerging preclinical evidence underscores associations between gut microbiota/microecological perturbations and IBD pathogenesis, with IBD itself recognised as a predisposing factor for malignancy[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Colorectal cancer (CRC), the third most prevalent malignancy worldwide, accounts for 10% of global cancer diagnoses and 9.4% of cancer-related mortality, ranking as the second leading cause of oncological death[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. While surgical resection remains the therapeutic cornerstone for CRC, postoperative bowel functional recovery is influenced by multifactorial determinants. Contemporary national and international studies on post-anaesthetic intestinal rehabilitation highlight key modulators, including minimally invasive surgical techniques, early enteral nutrition, and targeted probiotic supplementation[\u003cspan additionalcitationids=\"CR7\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. The adoption of Enhanced Recovery After Surgery (ERAS) protocols has further optimised postoperative bowel recovery in CRC patients[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Nevertheless, perioperative interventions\u0026mdash;such as mechanical bowel preparation, prophylactic antibiotic regimens, surgical trauma, and perioperative fluid management\u0026mdash;induce microbiota perturbations correlated with postoperative complications, including anastomotic leakage and surgical site infections[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Consequently, elucidating the interplay between gut microbiota dynamics and bowel functional outcomes in colorectal surgical patients represents a critical research imperative.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design and ethics\u003c/h2\u003e \u003cp\u003eA prospective study was conducted to investigate the role and impact of intestinal microbiota in recovery of bowel function for patients undergoing colon surgery. This study was approved by the Ethics committee of Peking University People\u0026rsquo;s Hospital (2022PHB053-001, Beijing, China). All patients provided written informed consent before participating in the study.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eParticipants\u003c/h3\u003e\n\u003cp\u003eAdult patients undergoing colorectal surgery at Peking University People\u0026rsquo;s Hospital between January 1st, 2023 and October 31th 2023 were eligible for inclusion. All patients were treated with oral laxatives for bowel preparation. The general anesthesia of all participants were intravenous propofol, remifentanil, and dexmedetomidine combined with inhalation of sevoflurane. All participants underwent preoperative bowel preparation with oral laxatives. General anaesthesia was administered using intravenous propofol, remifentanil, and dexmedetomidine in combination with inhaled sevoflurane. Perioperative infection prophylaxis comprised cefoperazone-sulbactam, while postoperative analgesia was achieved via opioid and non-steroidal anti-inflammatory drug regimens. Excluded criteria were defined as fellows:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003ePatients who had a history of surgical reconstruction of the gastrointestinal tract.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003ePatients who have used probiotics within the preceding 3 months.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003ePatients who were younger than 18 years.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003ePatients who withdrawal or refusal to participate.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eClinical data records were incomplete.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003ePrevious studies report a mean first postoperative defecation time of 5 days in colorectal surgery patients [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. In this study, participants were stratified into two cohorts: \u003cb\u003eGroup A\u003c/b\u003e (first postoperative defecation\u0026thinsp;\u0026le;\u0026thinsp;5 days) and \u003cb\u003eGroup B\u003c/b\u003e (first postoperative defecation\u0026thinsp;\u0026gt;\u0026thinsp;5 days).\u003c/p\u003e\n\u003ch3\u003eData collection\u003c/h3\u003e\n\u003cp\u003ePatient\u0026rsquo;s demographic variables\u0026mdash;including age, sex, and body mass index (BMI)\u0026mdash;were systematically recorded. Pre-existing comorbidities (e.g., hypertension, coronary heart disease [CHD], arrhythmia, cerebral infarction, intracranial haemorrhage, hypothyroidism, diabetes mellitus, chronic obstructive pulmonary disease [COPD], renal insufficiency, hyperlipidaemia, hepatic insufficiency, and haematological disorders) diagnosed prior to admission were documented in a case report form (CRF) Excel database. Data of preoperative chemotherapy, preoperative anemia, preoperative ileus, the American Society of Anesthesiologists (ASA) classification, bowel preparation before surgery (soapsuds enema, oral laxatives, glycerin enema, and oral antibiotics) were adopted in CRF. Data of surgery such as surgical site (right hemicolectomy, transverse colectomy, left hemicolectomy, sigmoid colectomy, and proc tectomy), surgical approach (laparotomy or laparoscopic surgery), duration of operation, and intraoperative bleeding were entered into CRF. Postoperative data including time of the first postoperative feeding (day), duration of analgesia and antibiotics, and hypoproteinemia were entered recorded. All data were obtained by medical record such as papery medical records library or electronic medical record system.\u003c/p\u003e\n\u003ch3\u003eStool sample collection\u003c/h3\u003e\n\u003cp\u003eFresh stool sample (not less 6 gram) were collected from participants and immediately stored at -80℃ at the time of the first postoperative defecation.\u003c/p\u003e\n\u003ch3\u003eMaterials and Methods for Metagenomics\u003c/h3\u003e\n\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eDNA extractions\u003c/h2\u003e \u003cp\u003e DNA was extracted using the E.Z.N.A.\u0026reg; Stool DNA Kit (D4015-02, Omega, Inc., USA) in accordance with the manufacturer\u0026rsquo;s guidelines. The reagent effectively isolates bacterial DNA from trace samples. Negative controls (unused swabs processed identically) confirmed no DNA contamination. Eluted DNA (50 \u0026micro;l) was stored at \u0026minus;\u0026thinsp;80\u0026deg;C prior to PCR analysis (LC-BIO, TECHNOLOGIES (HANGZHOU) CO., LTD., Hangzhou, Zhejiang Province, China), following a modified QIAGEN protocol.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eDNA Library Construction\u003c/h3\u003e\n\u003cp\u003eLibraries were constructed with the TruSeq Nano Kit (Illumina). DNA fragmentation used dsDNA Fragmentase (NEB) at 37\u0026deg;C/30 min. Blunt-end fragments were generated, size-selected with purification beads, and A-tailed for adapter ligation. Indexed adapters (T-overhang) enabled single/paired-end sequencing. PCR amplification conditions: 95\u0026deg;C/3 min; 8 cycles (98\u0026deg;C/15 s, 60\u0026deg;C/15 s, 72\u0026deg;C/30 s); 72\u0026deg;C/5 min.\u003c/p\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eData analysis\u003c/h2\u003e \u003cp\u003eRaw sequencing data were processed through adapter removal (Cutadapt), quality trimming (Fqtrim), and host DNA filtering (Bowtie2), followed by \u003cem\u003ede novo\u003c/em\u003e metagenome assembly (IDBA-UD). Coding sequences were predicted (MetaGeneMark), clustered into unigenes (CD-HIT), and quantified as TPM. Taxonomic classification (DIAMOND vs NCBI NR) and functional annotation (GO/KEGG/eggNOG/CAZy/CARD/PHI/MGEs/VFDB) were performed, with differential analysis (Fisher\u0026rsquo;s exact/Kruskal-Wallis tests) applied to taxonomic, functional, and gene-level features (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eUnivariate analysis was conducted using SPSS 26.0 software (IBM, Armonk, NY, USA) to identify potential risk factors influencing the timing of first postoperative defecation. Normally distributed quantitative data were expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD), while non-normally distributed variables were reported as medians and interquartile ranges (IQR), with between-group comparisons performed via one-way analysis of variance (ANOVA). Categorical variables were summarised as frequencies and percentages. For categorical data, statistical descriptions employed frequency and proportional composition, with intergroup comparisons assessed using the χ\u0026sup2; test or Fisher\u0026rsquo;s exact test, as appropriate.\u003c/p\u003e \u003cp\u003eVariables achieving statistical significance (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) in univariate analysis were entered into a multivariate logistic regression model employing backward stepwise elimination to identify independent predictors of delayed postoperative defecation. Odds ratios (OR) and corresponding 95% confidence intervals (CI) were calculated to quantify associations. A two-tailed \u003cem\u003ep\u003c/em\u003e-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was deemed statistically significant for all analyses.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eBaseline characteristics\u003c/h2\u003e \u003cp\u003ebetween January 1st, 2023 to October 31th 2023, 93 patients were assessed for eligibility, with 35 participants ultimately enrolled following exclusions (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Seven participants experienced a first postoperative defecation time exceeding 5 days. he cohort had a mean age of 62.49\u0026thinsp;\u0026plusmn;\u0026thinsp;11.74 years (ranged: 35\u0026ndash;87 years), with baseline clinical characteristics summarised in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Transverse colectomy (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.04), malignancy(\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.04), operative duration (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.01), and time of postoperative feeding(\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01) demonstrated statistically difference between groups in patients undergoing colorectal surgery.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline and characteristics of postoperative defection for patients undergoing colon surgery\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003evariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGroupA(\u0026le;\u0026thinsp;5day)\u003c/p\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;28\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGroupB(\u0026gt;\u0026thinsp;5day)\u003c/p\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;7\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eχ\u003csup\u003e2\u003c/sup\u003e/ t\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15(53.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3(42.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.61\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge(years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e61.43\u0026thinsp;\u0026plusmn;\u0026thinsp;12.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e66.71\u0026thinsp;\u0026plusmn;\u0026thinsp;7.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI\u003csup\u003ea\u003c/sup\u003e(kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24.34\u0026thinsp;\u0026plusmn;\u0026thinsp;3.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.21\u0026thinsp;\u0026plusmn;\u0026thinsp;3.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eASA\u003csup\u003eb\u003c/sup\u003e classification\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.44\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eⅠ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1(3.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eⅡ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24(85.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5(71.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eⅢ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3(10.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2(28.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProbiotics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8(28.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2(28.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRight colectomy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13(46.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2(28.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.39\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTransverse colectomy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1(3.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2(28.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLeft colectomy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2(7.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.47\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSigmoid colectomy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13(46.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3(42.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.87\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePreoperative ileus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5(17.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1(14.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.82\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6(21.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2(28.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.69\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCHD\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2(7.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.47\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes mellitus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7(25.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1(14.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCOPD\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1(3.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1(14.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMalignancy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28(100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6(85.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLaparotomy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4(14.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2(28.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.37\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDuration of operative (min)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e158.04\u0026thinsp;\u0026plusmn;\u0026thinsp;49.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e215.00\u0026thinsp;\u0026plusmn;\u0026thinsp;39.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntraoperative bleeding\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e53.93\u0026thinsp;\u0026plusmn;\u0026thinsp;38.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e94.26\u0026thinsp;\u0026plusmn;\u0026thinsp;135.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTime of postoperative feeding(day)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.36\u0026thinsp;\u0026plusmn;\u0026thinsp;0.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.86\u0026thinsp;\u0026plusmn;\u0026thinsp;1.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDuration of analgesia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.04\u0026thinsp;\u0026plusmn;\u0026thinsp;0.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.29\u0026thinsp;\u0026plusmn;\u0026thinsp;0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDuration of antibiotics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25(89.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7(100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.37\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypoproteinemia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10(35.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3(42.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.73\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003ea\u003c/sup\u003eBMI: Body mass index, \u003csup\u003eb\u003c/sup\u003eASA American society of Aneshesiologists, cCHD: Coronary atherosclerotic heart disease, \u003csup\u003ed\u003c/sup\u003eCOPD: Chronic obstructive pulmonary disease\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003ePrimary outcome. Multivariate analysis identified time to postoperative feeding as the sole independent risk factor for delayed defecation (19.53, 95%CI [1.80, 211.60]. \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.01).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eMicrobiome analysis\u003c/h2\u003e \u003cp\u003eMetaGeneMark software(v3.38) was employed to predict the CDS and assess biodiversity for contigs (\u0026ge;\u0026thinsp;500 bp) assembled per sample. Sequences with CDS lengths\u0026thinsp;\u0026lt;\u0026thinsp;100 nucleotides (nt) were filtered based on prediction outcomes. Subsequent clustering was performed at 95% sequence identity and 90% coverage, with the longest sequence selected as the representative to construct the Unigenes set. Comparative analysis revealed fewer Unigenes in patients with first postoperative defecation time\u0026thinsp;\u0026gt;\u0026thinsp;5 days versus those with \u0026le;\u0026thinsp;5 days, evident in both nucleic acid and protein sequence predictions (Additional file figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSpecies richness and community evenness were quantified using Chao1, Observed species, Shannon, and Simpson indices (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Rarefaction curve analysis, simulating resampling processes to estimate environmental species richness, demonstrated no statistically significant differences in alpha diversity indices between the \u0026le;\u0026thinsp;5-day and \u0026gt;\u0026thinsp;5-day cohorts (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAnalysis of Alpha diversity index of intestinal microbiome for patients undergoing colon surgery\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGroupA(\u0026le;\u0026thinsp;5day)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGroupB(\u0026gt;\u0026thinsp;5day)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChao1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e2482.90\u0026thinsp;\u0026plusmn;\u0026thinsp;804.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e2552.80\u0026thinsp;\u0026plusmn;\u0026thinsp;1021.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.65\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObserved_species\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e1914.60\u0026thinsp;\u0026plusmn;\u0026thinsp;662.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e1985.50\u0026thinsp;\u0026plusmn;\u0026thinsp;795.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.68\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eShannon\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e4.88\u0026thinsp;\u0026plusmn;\u0026thinsp;1.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e4.86\u0026thinsp;\u0026plusmn;\u0026thinsp;0.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.96\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSimpson\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.88\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e0.89\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.84\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eMicrobiome composition\u003c/h2\u003e \u003cp\u003eUnigenes protein sequences were aligned against the NR_meta library (a microbial-specific subset of the NCBI NR database comprising 52,375,954 sequences) using DIAMOND software (blastp; e-value\u0026thinsp;\u0026le;\u0026thinsp;1\u0026times;10⁻⁵). Species classification was assigned based on the highest-scoring match for each Unigene. Taxonomic abundance was calculated at each hierarchical level, with the top 20 most abundant species retained for visualisation; remaining taxa were aggregated as \"Others\".\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eSpecies richness analysis\u003c/h2\u003e \u003cp\u003eComparative taxonomic profiling revealed a lower proportion of probiotic taxa (e.g., Lactobacillus, Bifidobacterium) and elevated pathogenic bacteria in patients with prolonged postoperative defecation (\u0026gt;\u0026thinsp;5 days) versus the \u0026le;\u0026thinsp;5-day cohort. The \u0026le;\u0026thinsp;5-day group exhibited higher proportions of Bacteroidetes and Archaea, but reduced Proteobacteria, Firmicutes, Actinobacteriota, and Chytridiomycota in Phylum level (Additional file figure S2). Dominant taxa included Bacteroidia, Proteobacteria, Clostridia, Bacilli, Actinobacteria, and β-proteobacteria. The \u0026gt;\u0026thinsp;5-day cohort demonstrated increased Bacteroidia and α-proteobacteria, but diminished Proteobacteria, Bacilli, and Actinobacteria in Class level (Additional file Figure S3). Significant reductions in Lactobacillales and Enterobacterales were observed in the \u0026gt;\u0026thinsp;5-day group in Oder level (Additional file Figure S4). At the classification of Family, The \u0026gt;\u0026thinsp;5-day cohort showed reduced Enterobacteriaceae, Enterococcaceae, and Coriobacteriaceae, but elevated Klebsiellaceae and Mucoraceae (Additional file Figure S5). Depleted Enterococcus, Escherichia, Ruminococcus, and Bifidobacterium contrasted with enriched Klebsiella in the \u0026gt;\u0026thinsp;5-day group in Genus Level (Additional file Figure S6). At the species level, Probiotic taxa (Escherichia coli, Enterococcus faecalis, Bacteroides multivorans, Bifidobacterium spp., Clostridium prasicolum) were reduced, while pathogens (Bacteroides fragilis, Klebsiella pneumoniae, Bacteroides faecalis) predominated in delayed recovery patients (Additional file Figure S7).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eAnalysis of species richness differences\u003c/h2\u003e \u003cp\u003eUsing thresholds of |logFC| \u0026gt;1 and \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Proteobacteria, Firmicutes, Actinobacteria, Bacteroidetes, and viral taxa exhibited the greatest intergroup abundance disparities (Additional file Figure S8). It was found that the species abundance of Ruminococcus (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), Lachnospiraceae(\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), Escherichia_albertii(\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), and Escherichia_sp._4_140B(\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01) was lower in 5-day cohort. While the species abundance of Ruminococcaceae (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), Subdoligranulum (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), Bacteroidetes (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), Ruminococcaceae_bacterium (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01) was higher in 5-day cohort (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe contribution of the difference in species abundance for the time of postoperative defecation prolonged was obtained through the Random Forest algorithm. Gini Index analysis identified Alistipes AF48.12, Clostridium sp. AF12.41, Hyphomicrobiaceae bacterium, Paenibacillus sp. PY1325, Bacteroides spp., and Yersinia enterocolitica as key contributors to delayed postoperative defecation (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eFunctional annotation of intestinal microbiome metabolism\u003c/h2\u003e \u003cp\u003eI The top 30 GO terms with the smallest \u003cem\u003ep\u003c/em\u003e-values were selected from the Gene Ontology Consortium database to compare functional annotations of Unigene protein sequences between groups (Additional file Figure S9). Comparative analysis revealed significant reductions in Group B (\u0026gt;\u0026thinsp;5-day cohort) for the following processes: peptidase activity(\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), DNA replication initiation(\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), pyrimidine nucleobase metabolic process(\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), phosphate acetyltransferase activity(\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), glutamate biosynthetic process(\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), pyrimidine nucleoside salvage(\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), and enzyme-directed rRNA2\u0026rsquo;-O-methylation(\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFunctional annotation of Unigene protein sequences within the KEGG database demonstrated diminished carbohydrate metabolism, membrane transport, and amino acid metabolism in the \u0026gt;\u0026thinsp;5-day cohort. Key impaired pathways included: biosynthesis of secondary metabolites, microbial metabolism in diverse environments, cofactor biosynthesis, amino acids biosynthesis, two-component regulatory systems, ABC transporters, carbon metabolism, ribosomal function, purine metabolism, amino sugar and nucleotide sugar metabolism, quorum sensing, glycolysis/gluconeogenesis, starch and sucrose metabolism, pyruvate metabolism, pyrimidine metabolism, and galactomyces Sugar metabolism, cysteine and methionine metabolism, fructose and mannose metabolism, and oxidative phosphorylation in the group of patients with the time of first postoperative defecation\u0026thinsp;\u0026gt;\u0026thinsp;5days(Additional file Figure S10). At the KEGG Pathway Definition level, further analysis identified reduced activity in: Fiagellar assembly(\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), Glycolysis/Gluconeogenesis(\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), D-glutamine and D-glutamate metabolism (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), Cysteine and methiomine metabolism(\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), selenocompound metabolism(\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), Aminoacyl-tRNA biosynthesis(\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), protein export(\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), Peptidoglycan biosynthesis(\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), D-Alanine metabolism(\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), and pyrimidine metabolism(\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB).\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, metagenomic sequencing was performed on fecal specimens from the first postoperative defecation of patients after colon surgery to analyze gut microbiota composition, predominantly comprising Bacteroidetes, Proteobacteria, Firmicutes, and Actinobacteria. Patients with prolonged postoperative defecation time exhibited a reduced proportion of probiotic taxa and an elevated prevalence of pathogenic bacteria. However, no statistically significant intergroup differences in gut biodiversity were observed postoperatively. Functional annotation and comparative analysis of Unigene protein sequences across multiple databases revealed that delayed defecation was associated with impaired intestinal digestion/absorption capacity, diminished mucosal barrier integrity, and reduced epithelial repair mechanisms.\u003c/p\u003e \u003cp\u003eStudies investigating the gut microbiota-colorectal cancer axis have confirmed reduced microbial diversity in colorectal cancer patients. Research on postoperative anastomotic leakage further demonstrated that patients without leakage exhibited higher gut microbial diversity, whereas leakage correlated with diminished diversity and elevated Bacteroidaceae and Lachnospiraceae (notably Blautia) abundance [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. In this cohort, prolonged postoperative defecation time similarly corresponded to reduced microbial diversity. However, non-parametric intergroup comparisons of biodiversity indices lacked statistical significance, potentially attributable to the limited sample size of the \u0026gt;\u0026thinsp;5-day cohort (n\u0026thinsp;=\u0026thinsp;7). The widespread implementation of Enhanced Recovery After Surgery (ERAS) protocols and standardised perioperative care has shortened postoperative recovery milestones, including time to first flatus and defecation. An alternative explanation is that, despite delayed defecation, partial restoration of microbiota diversity and metabolic functions may commence during bowel movement recovery, potentially obscuring statistically significant correlations between microbial diversity and defecation timing in this analysis.\u003c/p\u003e \u003cp\u003eThe gut microbiota of healthy individuals is typically dominated by one archaeal phylum and five bacterial phyla: Bacteroidetes, Firmicutes, Actinobacteria, Proteobacteria, and Verrucomicrobia. Diets rich in sugar and animal fat but low in fibre correlate with elevated Bacteroidetes abundance, whereas high-fibre diets favour Firmicutes proliferation[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. In colorectal cancer (CRC), specific pathogens such as Fusobacterium nucleatum, Escherichia coli, Bacteroides fragilis, and Campylobacter jejuni drive tumourigenesis by fostering a pro-oncogenic microenvironment[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Bacteroides fragilis, a common gut symbiont critical for digestion and mucosal health, exists as two subtypes: non-toxigenic B. fragilis and enterotoxigenic B. fragilis (ETBF). ETBF secretes B. fragilis toxin (BFT), which disrupts epithelial integrity via E-cadherin cleavage, activates Wnt/β-catenin signalling, induces chronic inflammation, and promotes carcinogenesis. ETBF further upregulates spermine oxidase in colonocytes, amplifying reactive oxygen species (ROS) production, DNA damage, and CRC progression[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn this study, gut microbiota abundance was compared across six taxonomic levels (Phylum to Species) between patients with postoperative defecation times\u0026thinsp;\u0026le;\u0026thinsp;5 days (\u0026gt;\u0026thinsp;5-day cohort). Key findings included: elevated pathogens were Bacteroides fragilis, Ruminococcus spp., and Klebsiella pneumoniae in the \u0026gt;\u0026thinsp;5-day cohort. Depleted beneficial taxa were Enterococcus faecalis, Bifidobacterium spp., and Bacteroides thetaiotaomicron in delayed recovery patients.\u003c/p\u003e \u003cp\u003eRuminococcus (Gram-positive anaerobe; Lachnospiraceae family) degrades cellulose and carbohydrates, producing acetate and formate. While historically linked to Crohn\u0026rsquo;s disease and irritable bowel syndrome via butyrate metabolism[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], its paradoxical abundance in the \u0026le;\u0026thinsp;5-day cohort\u0026mdash;despite reduced carbohydrate metabolism in delayed patients\u0026mdash;suggests strain-specific functional heterogeneity warranting further investigation. Bacteroides is one of the dominant anaerobic geuns in the human gut. Its main function is to degrade large-molecule carbohydrates in plant foods into glucose and other easily digestible small-molecule sugars. acteroides, a dominant anaerobic genus, hydrolyses complex plant polysaccharides into absorbable sugars. Bacteroides thetaiotaomicron, encoding glycoside hydrolases and modulating glutamate metabolism, is pivotal for ileal/colonic mucosal health. Its depletion in the \u0026gt;\u0026thinsp;5-day cohort may impair carbohydrate processing and epithelial repair [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Bifidobacterium and Lactobacillus (common probiotics) inhibit harmful bacteria, enhance gut barrier integrity, and suppress pro-inflammatory cytokines Reduced Bifidobacterium and Lactobacillus (immunomodulatory probiotics) likely compromised gut barrier integrity and anti-inflammatory capacity [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Similarly, diminished Enterococcus faecalis(a Gram-positive facultative anaerobe used in dysbiosis therapy) may reflect impaired microbial resilience [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIt is well-established that gut microbiota predominantly interact with intestinal epithelial and stromal cells to maintain microenvironmental homeostasis. For instance, Bifidobacterium and Lactobacillus ferment fructooligosaccharides to produce lactate and acetate, which are subsequently metabolised by commensals such as Faecalibacterium into butyrate[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Butyrate serves as the principal energy substrate for colonic enterocytes. It enhances epithelial integrity by upregulating MUC2 (encoding mucin 2) and modulating tight junction protein expression, thereby fortifying the intestinal barrier. Additionally, butyrate lowers luminal pH, sustains microbial equilibrium, activates AMP-activated protein kinase (AMPK) to stimulate enterocyte differentiation, and reinforces mucosal defence mechanisms[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Beyond its metabolic roles, butyrate exhibits anti-inflammatory and anti-neoplastic properties through direct modulation of colonic cell metabolism and mucosal immunity[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Functional annotation of differentially expressed genes in this study revealed diminished carbohydrate metabolism in patients with delayed postoperative bowel recovery. This impairment likely stems from probiotic depletion, resulting in compromised dietary fibre processing, epithelial barrier dysfunction, and prolonged intestinal hypomotility.\u003c/p\u003e \u003cp\u003eDietary fibre degradation\u0026mdash;mediated by symbiotic bacteria such as Bacteroides via glycan-sensing enzymes\u0026mdash;generates short-chain fatty acids (SCFAs). SCFAs bind G protein-coupled receptors, inducing tolerogenic dendritic cell phenotypes, promoting regulatory T-cell (Treg) differentiation, polarising macrophages towards an M2 anti-inflammatory state, and stabilising gut homeostasis[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. In this cohort, reduced glycolysis/gluconeogenesis and fructose/mannose metabolism in delayed recovery patients correlated with attenuated immunomodulatory capacity in intestinal epithelia.\u003c/p\u003e \u003cp\u003eProbiotics enhance bile salt hydrolase (BSH) activity, catalysing taurine dissociation from tauro-conjugated bile acids[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. I The observed taurine metabolism deficit in delayed recovery patients may reflect probiotic insufficiency. Selenium, an essential trace element incorporated as selenocysteine (the 21st proteogenic amino acid), is critical for intestinal redox homeostasis. Selenoproteins\u0026mdash;including glutathione peroxidase, selenoprotein S, and selenoprotein P\u0026mdash;orchestrate antioxidant defences, mitigate oxidative stress, and suppress chronic inflammation[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Preclinical evidence indicates gut microbiota composition modulates host selenium bioavailability, influencing selenoprotein expression and inflammatory responses[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. The reduced selenocysteine incorporation observed in this study suggests impaired mucosal protection mechanisms in delayed recovery patients.\u003c/p\u003e \u003cp\u003eThis study investigated the role of gut microbiota in postoperative intestinal recovery following colorectal surgery through metagenomic sequencing of faecal samples obtained during the first postoperative bowel movement. Key limitations include:\u003c/p\u003e \u003cp\u003e(1) Sample Size Constraints: ① Rapid hospital discharge protocols, increasingly prevalent in recent years, have reduced inpatient stays to \u0026le;\u0026thinsp;7 days, complicating the collection of preoperative, intraoperative, and immediate postoperative faecal specimens. ② Suboptimal patient adherence\u0026mdash;particularly delayed reporting of bowel movements\u0026mdash;frequently precluded timely sample acquisition. ③ The prohibitive cost of metagenomic sequencing restricted cohort expansion (2) Mechanistic Ambiguities: Despite advancements in 16S rRNA and next-generation sequencing (NGS) technologies, which have catalysed discoveries in microbial diversity and host-microbe interactions, the precise mechanisms underpinning gut microbiota\u0026rsquo;s influence on intestinal function remain incompletely resolved. The gut microbiome encompasses a vast array of species with pleiotropic roles, ranging from direct mucosal crosstalk to systemic effects mediated via inflammatory cytokines and microbial metabolites. While implicated in pathologies such as chronic inflammation, oncogenesis, neuropsychiatric disorders, and metabolic diseases, current evidence remains insufficient to delineate causal pathways or molecular mediators. These gaps underscore the necessity for hypothesis-driven studies integrating multi-omics approaches (e.g., metabolomics, transcriptomics) to unravel microbiota-host dynamics in postoperative recovery.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eTimely resumption of enteral nutrition facilitates the restoration of postoperative bowel motility in patients undergoing colorectal surgery. A reduced proportion of probiotics and an increased abundance of pathogenic bacteria may delay the time of postoperative defecation for patients undergoing colon surgery. The reduction of metabolism in the bowel flora, namely the decrease of butyrate, taurine and selenocysteine, may prolong the recovery of postoperative bowel function for patients undergoing colon surgery.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIBD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eInflammatory bowel disease, CRC:Colorectal cancer, ERAS:Enhanced recovery after surgery, BMI:Body mass index\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCHD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCoronary heart disease\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCOPD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eChronic obstructive pulmonary disease\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eASA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAmerican Society of Anesthesiologists\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNSAIDs\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eNon-steroidal anti-inflammatory drugs\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCRF\u003c/div\u003e \u003cdiv class=\"Description\"\u003e\u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ecase report form\u003c/div\u003e \u003cdiv class=\"Description\"\u003e\u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCDS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCoding regions, SD:Standard deviations, OR:Odds ratios\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eConfidence intervals\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eGO\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eGene Ontology Consortium, KEGG:Kyoto Encyclopedia of Genes and Genomes, ETBF:Enterotoxigenic B. fragilis, ROS:Reactive oxygen species, MUC2:Mucin 2, Oligomeric Mucus/Gel-Forming, AMPK:Adenosine 5\u0026lsquo;-monophosphate-activated protein kinase, SCFAs:Short-chain fatty acids, BSH:Bile salt hydrolase.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSY and ZG designed the study. SY and YS participated in the literature search, analysis of data, as well as manuscript writing. YY participated in the literature search and data analysis and YA revised the manuscript. HZ and ZF participated in the data analysis and revised the manuscript. HZ had made contributions to the acquisition, analysis of data. SY and YS are equal the first author. YY and ZG are corresponding authors and are responsible for ensuring that all listed authors have approved the manuscript before submission. All authors approved the final manuscript for publication.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by National Nature Science Foundation of China (grant number 92478117).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data are available from the corresponding author on reasonable request. But the datasets are not are not publicly available due to privacy or ethical restrictions.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by medical ethics committee of Peking University People\u0026rsquo;s Hospital(2022PHB053-001). Conformed with the provisions of the Declaration of Helsinki. Written, informed consent was obtained from all patients\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declared no potential conflict of interest concerning the research, authorship, and/or publication of this article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThank you for all participants for accomplishing this study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eSender R, Fuchs S, Milo R: \u003cstrong\u003eAre We Really Vastly Outnumbered? 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Keilbaugh SA, Bewtra M, Knights D, Walters WA, Knight R\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eLinking long-term dietary patterns with gut microbial enterotypes\u003c/strong\u003e. \u003cem\u003eScience (New York, NY) \u003c/em\u003e2011, \u003cstrong\u003e334\u003c/strong\u003e(6052):105-108.\u003c/li\u003e\n\u003cli\u003eRen L, Ye J, Zhao B, Sun J, Cao P, Yang Y: \u003cstrong\u003eThe Role of Intestinal Microbiota in Colorectal Cancer\u003c/strong\u003e. \u003cem\u003eFrontiers in pharmacology \u003c/em\u003e2021, \u003cstrong\u003e12\u003c/strong\u003e:674807.\u003c/li\u003e\n\u003cli\u003eDejea C, Wick E, Sears CL: \u003cstrong\u003eBacterial oncogenesis in the colon\u003c/strong\u003e. \u003cem\u003eFuture microbiology \u003c/em\u003e2013, \u003cstrong\u003e8\u003c/strong\u003e(4):445-460.\u003c/li\u003e\n\u003cli\u003eCrost EH, Coletto E, Bell A, Juge N: \u003cstrong\u003eRuminococcus gnavus: friend or foe for human health\u003c/strong\u003e. \u003cem\u003eFEMS 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\u003cstrong\u003e9\u003c/strong\u003e(9).\u003c/li\u003e\n\u003cli\u003eKrumbeck JA, Rasmussen HE, Hutkins RW, Clarke J, Shawron K, Keshavarzian A, Walter J: \u003cstrong\u003eProbiotic Bifidobacterium strains and galactooligosaccharides improve intestinal barrier function in obese adults but show no synergism when used together as synbiotics\u003c/strong\u003e. \u003cem\u003eMicrobiome \u003c/em\u003e2018, \u003cstrong\u003e6\u003c/strong\u003e(1):121.\u003c/li\u003e\n\u003cli\u003eMa X, Fan PX, Li LS, Qiao SY, Zhang GL, Li DF: \u003cstrong\u003eButyrate promotes the recovering of intestinal wound healing through its positive effect on the tight junctions\u003c/strong\u003e. \u003cem\u003eJournal of animal science \u003c/em\u003e2012, \u003cstrong\u003e90 Suppl 4\u003c/strong\u003e:266-268.\u003c/li\u003e\n\u003cli\u003evan der Beek CM, Dejong CHC, Troost FJ, Masclee AAM, Lenaerts K: \u003cstrong\u003eRole of short-chain fatty acids in colonic inflammation, carcinogenesis, and mucosal protection and healing\u003c/strong\u003e. \u003cem\u003eNutrition reviews \u003c/em\u003e2017, \u003cstrong\u003e75\u003c/strong\u003e(4):286-305.\u003c/li\u003e\n\u003cli\u003eMoffa S, Mezza T, Cefalo CMA, Cinti F, Impronta F, Sorice GP, Santoro A, Di Giuseppe G, Pontecorvi A, Giaccari A: \u003cstrong\u003eThe Interplay between Immune System and Microbiota in Diabetes\u003c/strong\u003e. \u003cem\u003eMediators of inflammation \u003c/em\u003e2019, \u003cstrong\u003e2019\u003c/strong\u003e:9367404.\u003c/li\u003e\n\u003cli\u003eAhmadi S, Wang S, Nagpal R, Wang B, Jain S, Razazan A, Mishra SP, Zhu X, Wang Z, Kavanagh K\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eA human-origin probiotic cocktail ameliorates aging-related leaky gut and inflammation via modulating the microbiota/taurine/tight junction axis\u003c/strong\u003e. \u003cem\u003eJCI insight \u003c/em\u003e2020, \u003cstrong\u003e5\u003c/strong\u003e(9).\u003c/li\u003e\n\u003cli\u003eReeves MA, Hoffmann PR: \u003cstrong\u003eThe human selenoproteome: recent insights into functions and regulation\u003c/strong\u003e. \u003cem\u003eCellular and molecular life sciences : CMLS \u003c/em\u003e2009, \u003cstrong\u003e66\u003c/strong\u003e(15):2457-2478.\u003c/li\u003e\n\u003cli\u003eIvanov, II, Honda K: \u003cstrong\u003eIntestinal commensal microbes as immune modulators\u003c/strong\u003e. \u003cem\u003eCell host \u0026amp; microbe \u003c/em\u003e2012, \u003cstrong\u003e12\u003c/strong\u003e(4):496-508.\u003c/li\u003e\n\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":"Risk factor, Intestinal microbiota, Postoperative bowel function, Colorectal surgery","lastPublishedDoi":"10.21203/rs.3.rs-6637501/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6637501/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003ePurpose\u003c/h2\u003e \u003cp\u003eThis study aimed to investigate the risk factors and gut microbiome characteristics influencing postoperative bowel functional recovery in patients undergoing colorectal surgery.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003ePatients who underwent colorectal surgery between January 2023 and October 2023 were stratified into two cohorts based on the timing of their first postoperative defecation (\u0026le;\u0026thinsp;5 days vs. \u0026gt;5 days). Clinical data were systematically recorded, and identify independent risk factors associated with delayed bowel recovery. Fresh stool specimens were collected postoperatively and subjected to metagenomic sequencing to elucidate the relationship between gut microbiota composition and bowel functional outcomes.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThirty-five patients were enrolled in the study. Multivariate analysis identified time to first postoperative enteral feeding (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01) as the independent risk factor for delayed defecation. Alpha diversity indices revealed no significant intergroup differences in microbial species richness. However, patients with prolonged postoperative defecation time (\u0026gt;\u0026thinsp;5 days) exhibited a reduced proportion of probiotic taxa (e.g., Bifidobacterium, Lactobacillus) and an elevated prevalence of pathogenic bacteria compared to the \u0026le;\u0026thinsp;5-day cohort. Metagenomic profiling further demonstrated impaired microbial metabolic pathways in the delayed recovery group, notably diminished carbohydrate metabolism (e.g., glycolysis/gluconeogenesis) and amino acid metabolism (e.g., selenocysteine and taurine biosynthesis).\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eEarly postoperative resumption of enteral nutrition and probiotic may enhance bowel functional recovery. The observed reductions in microbial-driven gluconeogenesis/glycolysis, selenocysteine, and taurine synthesis suggest that dysregulation of these metabolic pathways may compromise intestinal mucosal repair and homeostasis, contributing to delayed postoperative recovery.\u003c/p\u003e","manuscriptTitle":"Effect of intestinal microbiota on the recovery of bowel function for patients undergoing colon surgery: a prospective cohort study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-10 15:38:07","doi":"10.21203/rs.3.rs-6637501/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":"681e8a3e-a708-4d54-b5af-590e4bd0e77c","owner":[],"postedDate":"June 10th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-07-14T08:08:55+00:00","versionOfRecord":[],"versionCreatedAt":"2025-06-10 15:38:07","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6637501","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6637501","identity":"rs-6637501","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}