Establishment of Post-Inflammatory Irritable Bowel Syndrome Animal Model Following Acute Colitis Recovery

Establishment of Post-Inflammatory Irritable Bowel Syndrome Animal Model Following Acute Colitis Recovery | 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 Article Establishment of Post-Inflammatory Irritable Bowel Syndrome Animal Model Following Acute Colitis Recovery Eui Sun Jeong, Hye-Kyung Jung, Euno Choi, Kyeongeui Yun, Ayoung Lee, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4680753/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 12 Mar, 2025 Read the published version in Scientific Reports → Version 1 posted 11 You are reading this latest preprint version Abstract Irritable bowel syndrome (IBS) is a prevalent disorder with an unclear pathophysiology. This study aimed to establish an experimental murine model of post-inflammatory IBS induced by acute severe colitis (acute model) or chronic mild repeated colitis (chronic model) to facilitate IBS analysis. The acute model was induced with 3% dextran sulfate sodium (DSS) for 5 days, followed by a 12-week recovery period. The chronic model involved administration of 0.5% DSS for 5 days, followed by a 5-day resting period, repeated thrice. We conducted comparative analyses to assess inflammation severity, intestinal motility, permeability, visceral hypersensitivity, and microbiome composition. In the acute model, mild leukocyte infiltration was observed, colonic transit time shortened at 12 weeks ( P < 0.001), occludin expression decreased ( P = 0.041), and inflammatory cytokines and transient receptor potential vanilloid 1 was upregulated in colonic mucosa ( P < 0.050). In the chronic model, only mild inflammatory changes were noted. Microbiota analysis in the acute model revealed differences in microbial abundance and compositions ( P = 0.001). The acute model effectively induced a post-inflammatory IBS model, characterized by low-grade inflammation that causes gut dysmotility, alters permeability, and increases visceral hypersensitivity with notable microbial composition changes. Health sciences/Gastroenterology/Gastrointestinal diseases Health sciences/Gastroenterology/Gastrointestinal models Health sciences/Diseases/Gastrointestinal diseases/Functional gastrointestinal disorders Irritable bowel syndrome Murine model Dextran sulfate sodium Low-grade inflammation Dysmotility Microbiome Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Introduction Irritable bowel syndrome (IBS) is a prevalent functional gastrointestinal disorder characterized by recurring abdominal pain associated with defecation or changes in bowel habits with no evidence of abnormalities in digestive organs. 1 The prevalence of IBS has been estimated to exceed 10% of the global population, 1 underscoring its significant medical concern. IBS substantially affects the quality of life of patients and places a considerable burden on the healthcare system. 2 IBS is a multifactorial disease and the precise pathophysiology is unclear. 3 The pathogenesis of IBS has focused on abnormalities in visceral hypersensitivity, motility, brain-gut interaction, and psychosocial distress, and more recently, altered immune activation, changes of gut permeability and microbiome have been demonstrated in a subset of IBS patients. 3 Additionally, the influence of diet and nutritional components further contributes to the intricate dynamics of IBS. Research on developing and validating animal models based on IBS pathophysiology has gained interest for the effective management of IBS. 3 Various animal models have been developed to study IBS, among which the stress-induced chronic visceral pain model is the most commonly used. However, these models possess limitations in fully replicating the complexity of human IBS. Wang et al. 4 proposed a rodent model involving central stimulation induced by water avoidance stress, restraint stress, and neonatal-maternal separation. Additionally, Moloney et al. 5 described two pain models: early-life stress-induced visceral pain using a maternal separation stress model and adult stress-induced visceral pain using acute or chronic water avoidance stress. Although these IBS animal models have contributed to the understanding of psychosocial or life-threatening stress, there is a need for versatile methods that can effectively address the complexities of IBS modeling while avoiding complex experimental setups and equipment, and adhering to animal research ethics. Another IBS model was the post-infectious induced IBS model. Long et al. 6 investigated visceral hyperalgesia and colonic muscle hypercontractility in IBS mice models induced by acute or chronic Trichinella spiralis infection. The activation of the immune system in colonic mucosa leads to immune cell infiltration and elevated levels of inflammatory cytokines, including interleukin (IL)-6, tumor necrosis factor (TNF)-α, and IL-1β in patients with IBS. 7 Similar to its application in inflammatory bowel disease (IBD), the post-inflammatory model emerges as a potential candidate for an IBS animal model, complementing those induced by psychological or life-threatening stress. Clinical symptoms overlap in patients with IBD who also present IBS-like symptoms. 8 The dextran sulfate sodium (DSS)-induced colitis mouse model has been widely used in IBD studies due to its ease of administration; 4 , 9 however, the exploration of experimental modeling specifically targeting low-grade inflammation related to IBS remains limited. Kodani et al. 10 analyzed gastrointestinal motility and macrophage/mast cell distribution during healing after induction of acute colitis with 2% DSS. However, similar to previous post-infectious IBS models, this study only analyzed changes following acute colitis, focusing on motility while not considering various other pathophysiological aspects of IBS, such as changes in visceral hypersensitivity, intestinal permeability, or microbial composition. Therefore, in this study, we aimed to induce post-inflammatory IBS from acute severe colitis or chronic mild repeated colitis using DSS and assess the suitability of the model by examining low-grade inflammation induced gut dysmotility, altered permeability, increased visceral hypersensitivity and notable changes in microbial composition in a simple and efficient manner. Materials and Methods Experimental Design Seven-week-old C57BL/6 male mice (Orient Bio Co., Ltd.®, Seongnam, Gyeonggi, Korea) were used in this study for IBS model induction. The mice were acclimated for 7 days at the Medical Research Center’s facility before experimentation. Mice were housed individually in standardized environmental conditions at 23 ± 2°C with 50–55% humidity and were allowed to feed food and drink ad libitum . The study protocol was approved by the Ethics Committee for Animal Research (EUM19-0456) and followed the ARRIVE 2.0 guidelines. Experimental procedures and results were conducted in accordance with regulations and guidelines. The mice were divided into two groups to induce the post-inflammatory IBS modeling: an acute severe colitis recovery IBS model (acute model) and a chronic mild repeated colitis IBS model (chronic model) (Fig. 1 ). For acute model, mice (n = 10) were administered with 3% DSS (MP biochemical®, Irvine, CA, USA) for 5 days, followed by a 12-week recovery period. During the recovery period, mice were given free access to food and water. The traditional IBD model involved a chronic model in which mice (n = 10) were orally administered with DSS for 5 days, followed by a recovery period of drinking water for the next 5 days, repeated for 3 cycles. To induce low-grade inflammation without causing gross mucosal damage, preliminary experiments were conducted to find an appropriate concentration of DSS, including 0.5%, 1.0%, and 1.5% for chronic models. Body weight changes, stool consistency, and gross bleeding were measured by the same observer every 7 days in the acute model and 3 days in the chronic model to assess disease activity, and the disease activity index (DAI) was calculated by adding the changes in body weight, stool consistency, and gross bleeding (Supplementary Table S1 ). 11 After completing the experiment in each model, all mice were euthanized through CO 2 asphyxiation after overnight fasting. After euthanasia, the entire colon was dissected from the cecum, and the total length was measured. Whole colon tissue was divided into proximal and distal sections, and then tissue from each section was split and analyzed by real-time polymerase chain reaction (RT-PCR), histopathology, and immunohistochemistry (IHC). Analysis of Intestinal Transit Time We used the gastrointestinal transit time (GITT) and the bead expulsion test to determine the intestinal transit time. For both techniques, we measured transit time before DSS administration and then every 4 weeks for the acute model and 30 days for the chronic model, respectively. Mice were housed individually to measure the GITT. A 6% solution of carmine red (natural red 4; Sigma Aldrich®, St. Louis, MO, USA), a non-absorbable dye, was administered through a 21-gauge gavage in 0.3 mL of 0.5% methylcellulose solution (Sigma Aldrich®). Following administration, mice were placed in a cage, the floors of which were lined with white paper to facilitate the carmine-red coloration of their feces. T 0 represented the time at which the carmine red solution was gavaged and the time it took for the expulsion of the first red fecal pellet was assessed. 12 In GITT measurements, closed-circuit television (CCTV) was employed as an auxiliary tool for more objective and accurate measurement. In the existing murine animal model, a bead expulsion test was a commonly used method to measure distal colonic transit time. 13 The distal colonic transit time was defined as the time between the bead insertion into the distal colon and its expulsion. Briefly, similar to previous studies, we dipped a single 2mm bead into the lubricating gel, gently inserted it, and measured the time to expulsion. RT-PCR analysis of Inflammatory Cytokines and Permeability Markers The mRNA expression of inflammatory cytokines in the mice colon, including IL-1β, IL-6, IL-17, and TNF-α was measured. We assessed the mRNA expression of occludin, zonular occludens (ZO)-1, claudin-1, and claudin-4 using RT-PCR 14 to assess the expression of the tight junction proteins in the IBS model RT-PCR was performed on proximal and distal colon sections. The separated colon tissue was immediately frozen at -70°C in a cryogenic freezer. Total RNA was isolated from colon tissue using the TRIzol reagent (Ambion®, Waltham, MA, USA). After adding chloroform (Sigma Aldrich®), the extracted total RNA was centrifuged at 12,000 rpm for 10 min at 4°C. The supernatants were centrifuged for 10 min at 12,000 rpm at 4°C with isopropanol (Sigma Aldrich®). After 75% ethanol wash, the pellet was solubilized with nuclease-free water and quantified using nano drops. RNA (2 µg) was reverse-transcribed in the mixture of oligo dT primers (0.5 µg), 200 units of Molony-Murine leukemia virus reverse transcriptase (Promega®, Fitchburg, WI, USA), 5x RT buffer, dNTPs (2 nM), and 25 units of RNasin ribonuclease inhibitor (Promega®) at 42 ℃ for 60 min. The RT-PCR was conducted on 7000 Real-time PCR systems (Applied Biosystems®, Waltham, MA, USA) with 2X Power SYBR Green PCR Master mix (Applied Biosystems®), 0.1 µg cDNA, and each primer set (Macrogen®, Seoul, Korea; Supplementary Table S2) over 40 cycles (95 ℃ for 15 s and 60 ℃ for 60 s) following pre-denature at 95 ℃ for 10 min. The relative expression of the target genes was assessed using the comparative Ct method, and glyceraldehyde-3-phosphate dehydrogenase was used as an internal control. Histopathological Analysis Histopathological examination was conducted by a single pathologist, and colon tissues were fixed in 10% formalin, followed by paraffin sectioning and hematoxylin-eosin (H&E) staining. Each colon tissue was stained with H&E and analyzed in three categories for histological evaluations: (i) inflammatory cell infiltrate, (ii) epithelial changes, and (iii) mucosal architecture. According to the criteria in histomorphological scores for intestinal inflammation in mouse models (Supplementary Table S3), each category was calculated with a score value ranging from 1 to 5. 15 Immunohistochemistry Analysis IHC analysis was performed, focusing on neuroinflammatory markers. Tissue samples were fixed in 4% paraformaldehyde in phosphate-buffered saline (pH 7.4), embedded in paraffin, and sectioned for IHC analysis. After deparaffinization and rehydration, antigen retrieval was performed by incubating the sections in citrate buffer (0.01 mmol/L, pH 6.0) and heating them in a microwave oven (720 W) for 15 min. Endogenous peroxidase was blocked by treating the sections in 0.3% hydrogen peroxide for 30 min at room temperature. Next, sections were incubated for 3 h at room temperature with specific antibodies: rabbit polyclonal transient receptor potential vanilloid 1 (TRPV 1) antibody (Invitrogen®, Waltham, USA), recombinant rabbit monoclonal tropomyosin receptor kinase A (TrkA) antibody (Invitrogen®), mouse monoclonal substance P antibody (Santa Cruz®, Dallas, TX, USA), rabbit monoclonal S-100 antibody (Leika®, Wetzlar, Germany), and mouse monoclonal neuron-specific enolase (NSE) antibody (Leika®) as visceral hypersensitivity markers. The sections were then incubated with horseradish peroxidase-conjugated goat anti-rabbit secondary antibodies for 30 min. The sections were then stained with 3,3-diaminobenzidine solution, followed by counterstaining with hematoxylin for nuclei labeling. 16 Immunopositive cells were counted using the Image J program (National Institutes of Health, Bethesda, MD, USA) in a 200 µm stretch of well-oriented entire colon epithelium sections at five randomly selective fields for each antibody. The average and standard deviation were subsequently calculated. 10 Microbiome Analysis We performed a microbiome analysis on the acute model selected as the IBS model based on comprehensive results. For microbiome analysis, intraluminal feces were collected from cecum of sacrificed mice and immediately frozen at -80 ℃. Microbial genomic DNA was extracted using QIAamp PowerFecal Pro DNA Kit (Qiagen®, Hilden, North Rhine-Westphalia, Germany), following the recommended protocols. The quality of all extracted bacterial genomic DNA was assessed using the Qubit 4 (ThermoFisher Scientific®, Waltham, MA, USA). The extracted mitochondrial DNA samples were stored at 4°C until further processing. The DNA sequencing library targeting the V3 and V4 hypervariable regions of 16S ribosomal RNA was constructed according to the sequencing library preparation protocol (Illumina®, San Diego, CA, USA) using specific universal primers (Illumina 16S forward 341F primer, 5'-TCGTCGGCAGCGTCAGATGTGTATAAGAGACAGCCTACGGGNGGCWGCAG − 3' and reverse 805R primer, 5'-GTCTCGTGGGCTCGGAGATGTGTATAAGAGACAG GACTACHVGGGTATCTAATCC-3'). 17 PCR was carried out using KAPA HiFi HotStart ReadyMix (Kapa Biosystems®, Wilmington, MA, USA), followed by purification of the PCR product with AMPure XP beads (Beckman Coulter Genomics®, Brea, CA, USA). An additional PCR amplification was performed to introduce the Illumina adapter and multiplex indices using the Nextera XD Index (Illumina®). The final PCR products were purified once again using the AMPure XP beads. The prepared library was then sequenced using the Miseq system (Illumina®) with 300 bp paired-end reads. The gut microbiome data was analyzed using the QIIME2 pipeline plugin (2022.08). 18 Before implementing DADA2 (Divisive Amplicon Denoising Algorithm 2) in QIIME2, Figaro was used to determine optimal options based on sequence quality. 19 Amplicon sequence variants (ASVs) were obtained through the denoising step in the DADA2 algorithm. The ASVs were subjected to bacterial classification using a Naïve Bayes classifier based on targeted hypervariable reads extracted from the SILVA 138v 99% rRNA database to improve accuracy. Subsequently, various features annotated with Archaea, Eukaryotes, Mitochondria, or Chloroplasts were removed. The selected bacterial features were employed for the construction of a phylogeny tree using the align-to-tree-mafft-fasttree plugin, and taxonomy composition was determined. These features were rarefied at a specified depth and utilized for the analysis of alpha diversity, including Observed Features, Chao1 Index, Shannon's Index, Simpson's Index, and Pielou's Evenness, as well as beta diversity, encompassing Bray-Curtis and Unweighted UniFrac metrics. 20 Statistical analysis Statistical Package for the Social Sciences (SPSS) program, version 25.0 software (SPSS Inc.®, Chicago, IL, USA) was used for all statistical analysis. The mean ± standard deviation values were used for each analysis. Comparisons of values between the models were tested using the nonparametric Kruskal–Wallis test. Graphical representations were generated using GraphPad Prism software version 8 (GraphPad Software Inc.®, La Jolla, CA, USA). A P -value of < 0.050 was considered statistically significant. For microbiome analysis, statistical significance in group comparisons for α-diversity and taxonomy composition was evaluated using the Mann-Whitney U-test (Wilcoxon Rank-sum test) in R through the 'ggpubr' package. To confirm the similarity between groups in distance matrices from β-diversity, principal coordinate analysis and permutational analysis of variance with 999 permutations were performed using the ‘Vegan’ and ‘Adonis’ packages in R. Additionally, linear discriminant analysis effect size (LEfSe) was calculated and features with a linear discriminant analysis score ≥ 2.0 were considered significant within each group. 21 Results Changes in the DAI of the IBS Models In the acute model, the body weight decreased by 10.1 ± 3.1% in the two weeks, then gradually increased and recovered in four weeks. The average DAI score was elevated at two weeks after DSS administration (6.8 ± 1.1), and no disease activity was observed after four weeks (Fig. 2 A). In the chronic model, body weight increased in the control, 0.5%, and 1.0% DSS groups but decreased by 3.2 ± 7.6% in the 1.5% DSS group. Gross bleeding was observed only in the 1.0% DSS group (0.3 ± 0.6), whereas diarrhea or loose stool was observed in the 1.0%, 1.5%, and 0.5% DSS groups. The DAI scores were higher in the 1.0% and 1.5% DSS groups (5.3 ± 1.5 and 4.5 ± 2.1, respectively) than in the 0.5% DSS group (1.0 ± 0.0; Fig. 2 B). Changes in Colon Length in the IBS Models The colon length did not differ between the acute model and the control (99.5 ± 7.9 mm vs. 103.0 ± 9.6 mm, P = 0.420). In the chronic model, the colon length in the 0.5% DSS group did not show significant differences from the control (92.9 ± 6.6 mm vs. 103.0 ± 9.6 mm, P = 0.264); however, those in the 1.0% and 1.5% DSS groups ( P = 0.009 and P = 0.036) decreased significantly (Fig. 2 C, 2 D). Changes in Colon Transit Time in the IBS Models In the acute model, GITT slowed compared to the control group up to 8 weeks after colitis induction but significantly accelerated by 12 weeks (146.9 ± 40.2 min vs. 221.0 ± 25.0 min, P < 0.001; Fig. 3 A). In the chronic model, no significant change in transit time was observed compared to the control after 30 days (157.0 ± 33.2 min vs. 151.2 ± 38.4 min, P = 0.937; Fig. 3 C). Moreover, no significant difference was observed in distal colon transit by bead expulsion test between the IBS models and the controls (Fig. 3 B, 3 D). Expression of Inflammatory Cytokine mRNAs in the IBS Models In the proximal colon of the acute model, the mean mRNA expression of IL-1β and IL-17 were increased compared to those in the controls (2.0 ± 0.7 vs. 1.2 ± 0.8, P = 0.034 for IL-1β; Fig. 4 A, 2.5 ± 2.9 vs. 1.0 ± 0.7, P = 0.041 for IL-17; Fig. 4 B). In the distal colon of the acute model, the mean mRNA expression of IL-1β, IL-17, and TNF-α showed a significant increase compared to those in the controls (2.1 ± 1.4 vs. 1.0 ± 0.5, P = 0.049 for IL-1β; Fig. 4 E, 2.9 ± 3.3 vs. 1.1 ± 0.8, P = 0.028 for IL-17; Fig. 4 F, and 2.0 ± 1.1 vs. 1.0 ± 0.3, P = 0.018 for TNF-α; Fig. 4 G). In the distal colon of the chronic model, a significant increase in the mean mRNA expression of IL-17 compared to that in the controls (2.3 ± 1.7 vs. 1.1 ± 0.5, P = 0.026; Fig. 4 F). However, no remarkable increase in the expression of the inflammatory cytokines was observed in the proximal colon of the chronic model compared to that in the controls. Expression of Tight Junction Protein coding mRNAs in the IBS Models Compared to that in the controls, the expression of occludin mRNA in the proximal colon was only significantly decreased in the acute model (0.9 ± 0.4 vs. 1.5 ± 0.8, P = 0.041; Fig. 4 D). In both models, the expression of ZO-1, claudin-1, and claudin-4 mRNAs did not differ from their expression in controls (Supplementary Fig. S1 A-F). Histopathological Evaluation in the IBS Models The inflammatory severity and extent in colon tissue were evaluated using H&E stain (Supplementary Fig. S2). In both models, the colon tissue was observed to be grossly normal. The mild leukocyte infiltration was mainly observed in the distal colon of both models. Expression of Neuroinflammatory Markers in the IBS Models In both the acute model and the control, the expression of TRPV 1 and TrkA in the colonic epithelium was observed. Scattered and weak IHC staining was observed on the basolateral membrane of epithelial cells, while inflammatory cells in the epithelium and lamina propria showed relatively strong TRPV 1 and TrkA expressions in the acute model. Quantitative analysis using the Image J program revealed increased immunopositivity in TRPV 1 and TrkA in the acute model compared to that in the controls (412.2 ± 80.1 vs. 72.6 ± 21.4, P = 0.008 for TRPV 1 and 392.6 ± 63.4 vs. 96.2 ± 14.2, P = 0.008 for TrkA) (Fig. 5 A, 5 B). However, immunopositivity of substance P, S100, and NSE was rarely detected in the acute model (Supplementary Fig. S3A, 3B, and 3C). In contrast, in the chronic model, none of the markers showed significant differences in expression compared to controls (64.6 ± 13.6 vs. 48.4 ± 10.8, P = 0.095 for TRPV 1; 67.2 ± 16.5 vs. 75.2 ± 11.8, P = 0.310 for TrkA) (Fig. 5 A, 5 B and Supplementary Fig. S3). Comparative Analysis of Microbiomes in Control and the IBS model The alpha-diversity analysis, encompassing Observed features, Chao1 index, Shannon's index, Simpson's index, and Pielou's evenness, did not reveal a significant difference in the level of diversity within individual samples between the acute model and the controls ( P > 0.050; Fig. 6 A). However, the beta-diversity analysis between the two groups indicated notable differences in both Bray-Curtis dissimilarity ( P = 0.001) and Unweighted UniFrac dissimilarity ( P = 0.001), reflecting distinct microbial composition and dissimilarity (Fig. 6 B). At the genus level, 16 genera exhibited statistically significant differences between the two groups ( P < 0.050). LFfSe analysis revealed a higher abundance of Lachnospiraceae , Erysipelatoclostridium , [Eubacterium] xylanophilum , Colidextribacter , Ruminococcaceae UBA1819 , Marvinbryantia , Anaerotruncus , and Turicibacter in the acute model compared to that in the control. Conversely, Clostridium sensu stricto 1 , Ruminococcus , Bifidobacterium , Clostridia UCG-014 , Anaeroplasma , [Eubacterium] fissicatena , and Romboutstia exhibited a relatively higher abundance in the control group than that in the acute model (Fig. 7 ). These results showed no difference in the alpha diversity between the acute model and the control; however, noticeable changes in microbial composition were observed in the acute model. Discussion In this study, we successfully established a post-inflammatory IBS murine model using a recovery model after inducing acute severe colitis. The model was developed by inducing acute severe colitis with 3% DSS and allowing a recovery period of 12 weeks. However, chronic mild repeated colitis induced modeling was not demonstrated as a post-inflammatory IBS model. The criteria for a valid post-inflammatory IBS animal model include the absence of clinical signs of organic abnormalities (such as hematochezia, significant weight loss, or shortening of colon length), low-grade inflammatory changes without overt histological findings of colitis, and the presence of surrogate markers for IBS-related pathophysiology (such as gastrointestinal dysmotility or visceral hypersensitivity). Our post-inflammatory IBS murine model exhibited activation of low-grade inflammatory cytokines, decreased GITT, increased expression of neuroinflammatory markers, and microbial composition change without clinical and histological manifestations of organic colonic disorders. In comparison to various previous IBS animal models 4 , the stress-induced chronic visceral pain model has been commonly utilized. However, these models could pose ethical limitations due to the use of physical stressors like restraint, water avoidance, and neonatal-maternal separation in rodents. 4 , 22 Animal models of IBS with other mechanisms have been investigated, including several post-infectious IBS animal models caused by bacterial and parasitic infections such as Campylobacter jejuni , Salmonella enterica , or Trichinella spiralis . 4 , 23 , 24 However, since post-infectious IBS is influenced by pathogens, there is a limitation that the symptoms in murine models induced by bacterial or parasitic pathogens may differ from those of actual human post-infectious IBS. 24 On the other hand, the representative post-inflammatory IBS model using trinitrobenzene sulfonic acid has the limitation of lacking a standardized protocol regarding dosage, concentration, and administration site. 24 Therefore, a new methodology of IBS animal modeling was required. Our approach aimed to establish a post-inflammatory IBS murine model by inducing low-grade inflammation using DSS, a method that is easily used for establishing IBS animal models. 25 , 26 Referring to the previous DSS-induced IBD murine model, we conducted experiments to induce low-grade inflammation by administering high concentrations of DSS for a short period or repeated low concentrations. 25 To evaluate bowel motility changes, we measured the change in intestinal transit time in vivo . 9 In our IBS model, the GITT analysis using real-time CCTV showed that the transit time increased until 8 weeks after high-dose DSS administration and significantly decreased after 12 weeks compared to the controls. Similar to our study, a previous study reported changes in colonic motility following recovery from alterations in the mucosal immune system. 10 Our findings also demonstrated mild leukocyte infiltration in the lamina propria in both the acute and chronic models. Because various inflammatory cytokines were elevated in the acute model compared to those in the chronic model, we speculated that low-grade inflammation in the acute model may affect the enteric immune system, leading to the establishment of the IBS model. Additionally, we considered that the increase in IL-17 expression in the acute model, which can enhance intestinal muscle contractility, might affect colonic motility. 27 The expression of the tight junction protein occludin decreased in the proximal colon of the acute model, whereas no notable differences were observed in the chronic model. Previous studies have also reported that intestinal permeability was related to tight junction proteins, and occludin plays a major role in IBS. 28 , 29 Coëffier et al. 28 demonstrated that proteasome alterations enhance intestinal permeability due to decreased occludin expression in IBS. Furthermore, increased levels of IL-1β mRNA have been shown to reduce the occludin expression and increase intestinal permeability in a colitis mouse model. 29 Concordant with these studies; our study also demonstrates decreased occludin expression induced by IL-1β overexpression. Visceral hypersensitivity is an important pathogenesis of IBS and can be induced by various pathophysiological abnormalities. To indirectly predict visceral hypersensitivity, we used IHC staining for several neuroinflammatory markers known to be associated with visceral hypersensitivity in previous studies. In the human IBS study, TRPV 1 expression was shown to be elevated in the mucosal nerve fibers and correlated with the abdominal pain score. 30 TrkA is a nerve growth factor that mediates nerve fiber growth and pain transmission. 31 In addition, substance P, S100 protein, and NSE were over-expressed in IBS patients. 4 The IHC staining results for these markers showed that TRPV 1 and TrkA immunopositivity was quantitatively higher only in the acute colitis model. Therefore, we could indirectly predict that our IBS model might have increased visceral hypersensitivity. Several studies have posited that microbial alterations play a role in the pathogenesis of IBS. In our acute model, we observed an increase in the abundance of Lachnospiraceae and Ruminococcaceae , indicating differences in microbial composition and dissimilarity. Jeffery et al. 32 reported that Lachnospiraceae alters the function of the mucous barrier, and Ruminococcaceae produces abundant short-chain fatty acids associated with visceral hypersensitivity–both these factors may contribute to the induction of IBS. While the specific gut microbiota groups influencing the etiology of IBS remain to be precisely elucidated, our model demonstrates the potential to serve as a novel IBS model compared to earlier research. The strength of our model is that it was constructed using a relatively simple method compared to previous animal IBS models. Additionally, we conducted in vivo studies from various perspectives to evaluate the mechanism of the post-inflammatory IBS model induced by low-grade inflammation changes. Despite this strength, our models have certain limitations. We did not specifically address the potential impact of sex in each model, and our measurements focused on whole gut transit and distal colon transit rather than precise colon transit time. However, previous in vivo studies of GITT in mice using magnetic resonance imaging showed high construct validity with the human study. 33 Another limitation is that we did not directly measure colorectal distension to predict visceral hypersensitivity. Instead, we used IHC staining for neuroinflammation markers to indirectly predict visceral hypersensitivity. In conclusion, the acute model induced the post-inflammatory IBS experimental model, demonstrating low-grade inflammation, gut dysmotility, changes in permeability, and increased visceral hypersensitivity with notable microbial composition changes. This experimental modeling holds promise for diverse IBS studies, allowing investigations into pathophysiological mechanisms and targeted therapies in the future. Declarations Data availability The datasets used and/or analyzed in the current study are available from the corresponding author on reasonable request. Acknowledgment This study was supported by a KSNM grant of the Korean Society of Neurogastroenterology and Motility for 2022. Author contributions E.S.J., H.K.J.: research conceptualization, experimental methodology, experiment, data analysis, drafting of the manuscript;E.S.J., H.K.J., A.Y.L., Y.S.K.: review and editing of the manuscript; E.N.C.: pathologic analysis and review; K.E.Y, Y.S.K.: microbiome experiment and analysis. All authors reviewed the manuscript. References Holtmann, G. J., Ford, A. C. & Talley, N. J. Pathophysiology of irritable bowel syndrome. The lancet Gastroenterology & hepatology 1, 133–146 (2016). Lembo, A. J. The clinical and economic burden of irritable bowel syndrome. Pract Gastroenterol 31, 3–9 (2007). Drossman, D. A. Functional gastrointestinal disorders: history, pathophysiology, clinical features, and Rome IV. Gastroenterology 150, 1262–1279. e1262 (2016). Wang, Y. et al. Rodent model of irritable bowel syndrome. Int. J. Gastroenterol. Disord. Ther 4, 131 (2017). Moloney, R. D., O'Mahony, S. M., Dinan, T. G. & Cryan, J. F. Stress-induced visceral pain: toward animal models of irritable-bowel syndrome and associated comorbidities. Front Psychiatry 6, 15 (2015). https://doi.org:10.3389/fpsyt.2015.00015 Long, Y., Liu, Y., Tong, J., Qian, W. & Hou, X. Effectiveness of trimebutine maleate on modulating intestinal hypercontractility in a mouse model of postinfectious irritable bowel syndrome. European Journal of Pharmacology 636, 159–165 (2010). https://doi.org:https://doi.org/10.1016/j.ejphar.2010.03.037 Lazaridis, N. & Germanidis, G. Current insights into the innate immune system dysfunction in irritable bowel syndrome. Annals of gastroenterology 31, 171 (2018). Halpin, S. J. & Ford, A. C. Prevalence of Symptoms Meeting Criteria for Irritable Bowel Syndrome in Inflammatory Bowel Disease: Systematic Review and Meta-Analysis. Official journal of the American College of Gastroenterology | ACG 107, 1474–1482 (2012). https://doi.org:10.1038/ajg.2012.260 Chassaing, B., Aitken, J. D., Malleshappa, M. & Vijay-Kumar, M. Dextran sulfate sodium (DSS)-induced colitis in mice. Curr Protoc Immunol 104, 15.25.11–15.25.14 (2014). https://doi.org:10.1002/0471142735.im1525s104 Kodani, M. et al. Association between gastrointestinal motility and macrophage/mast cell distribution in mice during the healing stage after DSS–induced colitis. Molecular medicine reports 17, 8167–8172 (2018). Ito, R. et al. Interferon-gamma is causatively involved in experimental inflammatory bowel disease in mice. Clin Exp Immunol 146, 330–338 (2006). https://doi.org:10.1111/j.1365-2249.2006.03214.x Li, Z. et al. Essential roles of enteric neuronal serotonin in gastrointestinal motility and the development/survival of enteric dopaminergic neurons. Journal of Neuroscience 31, 8998–9009 (2011). Kishi, K., Kamizaki, M., Kaji, N., Iino, S. & Hori, M. A close relationship between networks of interstitial cells of Cajal and gastrointestinal transit in vivo. Frontiers in Pharmacology 11, 587453 (2020). Turner, J. R., Buschmann, M. M., Romero-Calvo, I., Sailer, A. & Shen, L. in Seminars in cell & developmental biology. 204–212 (Elsevier). Erben, U. et al. A guide to histomorphological evaluation of intestinal inflammation in mouse models. International journal of clinical and experimental pathology 7, 4557 (2014). Luo, C. et al. Upregulation of the transient receptor potential vanilloid 1 in colonic epithelium of patients with active inflammatory bowel disease. International journal of clinical and experimental pathology 10, 11335 (2017). Bukin, Y. S. et al. The effect of 16S rRNA region choice on bacterial community metabarcoding results. Scientific Data 6, 1–14 (2019). Bolyen, E. et al. Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nature biotechnology 37, 852–857 (2019). Callahan, B. J. et al. DADA2: High-resolution sample inference from Illumina amplicon data. Nature methods 13, 581–583 (2016). Weinstein, M. M., Prem, A., Jin, M., Tang, S. & Bhasin, J. M. FIGARO: An efficient and objective tool for optimizing microbiome rRNA gene trimming parameters. bioRxiv , 610394 (2019). Chang, F., He, S. & Dang, C. Assisted selection of biomarkers by linear discriminant analysis effect size (LEfSe) in microbiome data. JoVE (Journal of Visualized Experiments), e61715 (2022). Greenwood-Van Meerveld, B., Prusator, D. K. & Johnson, A. C. Animal models of gastrointestinal and liver diseases. Animal models of visceral pain: pathophysiology, translational relevance, and challenges. American Journal of Physiology-Gastrointestinal and Liver Physiology 308, G885-G903 (2015). Beatty, J. K., Bhargava, A. & Buret, A. G. Post-infectious irritable bowel syndrome: mechanistic insights into chronic disturbances following enteric infection. World journal of gastroenterology: WJG 20, 3976 (2014). Qin, H.-Y. et al. Systematic review of animal models of post-infectious/post-inflammatory irritable bowel syndrome. Journal of gastroenterology 46, 164–174 (2011). Perše, M. & Cerar, A. Dextran sodium sulphate colitis mouse model: traps and tricks. Journal of Biomedicine and Biotechnology 2012 (2012). Kodani, M. et al. Association between gastrointestinal motility and macrophage/mast cell distribution in mice during the healing stage after DSS–induced colitis. Mol Med Rep 17, 8167–8172 (2018). https://doi.org:10.3892/mmr.2018.8926 Andoh, A., Ogawa, A., Bamba, S. & Fujiyama, Y. Interaction between interleukin-17-producing CD4 + T cells and colonic subepithelial myofibroblasts: what are they doing in mucosal inflammation? Journal of gastroenterology 42, 29–33 (2007). Coëffier, M. et al. Increased proteasome-mediated degradation of occludin in irritable bowel syndrome. Official journal of the American College of Gastroenterology| ACG 105, 1181–1188 (2010). Rawat, M. et al. IL1B increases intestinal tight junction permeability by up-regulation of MIR200C-3p, which degrades occludin mRNA. Gastroenterology 159, 1375–1389 (2020). Akbar, A. et al. Increased capsaicin receptor TRPV1-expressing sensory fibres in irritable bowel syndrome and their correlation with abdominal pain. Gut 57, 923–929 (2008). Jardí, F., Fernández-Blanco, J. A., Martínez, V. & Vergara, P. Plasticity of dorsal root ganglion neurons in a rat model of post-infectious gut dysfunction: potential implication of nerve growth factor. Scandinavian journal of gastroenterology 49, 1296–1303 (2014). Jeffery, I. B., Quigley, E. M., Öhman, L., Simrén, M. & O'Toole, P. W. The microbiota link to irritable bowel syndrome: an emerging story. Gut Microbes 3, 572–576 (2012). https://doi.org:10.4161/gmic.21772 Schwarz, R., Kaspar, A., Seelig, J. & Künnecke, B. Gastrointestinal transit times in mice and humans measured with 27Al and 19F nuclear magnetic resonance. Magnetic Resonance in Medicine: An Official Journal of the International Society for Magnetic Resonance in Medicine 48, 255–261 (2002). Additional Declarations No competing interests reported. Supplementary Files 3.SupplementaryInformationJeongetal240703.docx Cite Share Download PDF Status: Published Journal Publication published 12 Mar, 2025 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 29 Oct, 2024 Reviews received at journal 28 Oct, 2024 Reviewers agreed at journal 24 Oct, 2024 Reviews received at journal 06 Sep, 2024 Reviewers agreed at journal 25 Aug, 2024 Reviewers agreed at journal 25 Aug, 2024 Reviewers invited by journal 23 Jul, 2024 Editor assigned by journal 23 Jul, 2024 Editor invited by journal 12 Jul, 2024 Submission checks completed at journal 08 Jul, 2024 First submitted to journal 03 Jul, 2024 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-4680753","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":333600922,"identity":"5e74286f-e920-4616-b1a3-a583ae40b81e","order_by":0,"name":"Eui Sun Jeong","email":"","orcid":"","institution":"Ewha Womans University","correspondingAuthor":false,"prefix":"","firstName":"Eui","middleName":"Sun","lastName":"Jeong","suffix":""},{"id":333600923,"identity":"7b6bf8f5-5554-4f43-8108-3636286b78ed","order_by":1,"name":"Hye-Kyung Jung","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAzklEQVRIiWNgGAWjYBACxgYGBmaGAzYMDBIQAQNitaSRoAUEgFoOk6CFeUbu4dcFZ87LGdxufsDwo4bB2LyBkMNm5KVZz7hx29jgzjEDxp5jDGYyBwhqyTEz5vlwO3HbjQQDBt4GBhsJQg6DajlXv+1G+gfGv0RqMX7Mc+NAgtmNHANmoC1mhLX0vDFj5jmTbLj/Rk7BYZljEsYEtRi25xh/5jlmJy85I33jwzc1NoYzCGppYGCDm3sAHjv4gDwwaj4QVjYKRsEoGAUjGgAAISlAXWChbPQAAAAASUVORK5CYII=","orcid":"","institution":"Ewha Womans University","correspondingAuthor":true,"prefix":"","firstName":"Hye-Kyung","middleName":"","lastName":"Jung","suffix":""},{"id":333600924,"identity":"87d5a539-dc90-4bd4-856e-8938e5d918d5","order_by":2,"name":"Euno Choi","email":"","orcid":"","institution":"Ewha Womans University","correspondingAuthor":false,"prefix":"","firstName":"Euno","middleName":"","lastName":"Choi","suffix":""},{"id":333600925,"identity":"a92b9a62-a2c9-4cff-92bc-a47e822bcb8f","order_by":3,"name":"Kyeongeui Yun","email":"","orcid":"","institution":"HuNBiome Co., Ltd","correspondingAuthor":false,"prefix":"","firstName":"Kyeongeui","middleName":"","lastName":"Yun","suffix":""},{"id":333600926,"identity":"357573b3-62bc-4069-8418-2911ed709123","order_by":4,"name":"Ayoung Lee","email":"","orcid":"","institution":"Korea University","correspondingAuthor":false,"prefix":"","firstName":"Ayoung","middleName":"","lastName":"Lee","suffix":""},{"id":333600927,"identity":"dd510c0e-6939-4f9e-8c4f-342680fba0c2","order_by":5,"name":"Yung Sung Kim","email":"","orcid":"","institution":"Wonkwang University","correspondingAuthor":false,"prefix":"","firstName":"Yung","middleName":"Sung","lastName":"Kim","suffix":""}],"badges":[],"createdAt":"2024-07-03 13:31:20","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4680753/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4680753/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-025-88981-7","type":"published","date":"2025-03-12T15:57:34+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":61465025,"identity":"8cf6f372-468b-49de-8d1a-34a895ec7010","added_by":"auto","created_at":"2024-07-31 05:35:50","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":58034,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eExperimental design for post-inflammatory irritable bowel syndrome (IBS) animal model. \u003c/strong\u003e(A) Acute severe colitis recovery IBS model (acute model), 3% dextran sulfate sodium (DSS) was administered for 5 days followed by a 12-week recovery period . (B) Chronic mild repeated colitis IBS model (chronic model), 0.5% DSS was administered for 5 days, followed by a 5-day resting period, repeated three times over 30 days.\u003c/p\u003e\n\u003cp\u003eGITT, gastrointestinal transit time; BET, bead expulsion test; RT-PCR, real-time polymerase chain reaction; H\u0026amp;E stain, hematoxylin-eosin stain; IHC, immunohistochemistry.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4680753/v1/b52007fb386a30c521579086.png"},{"id":61465030,"identity":"6b2e57b3-bb2a-4166-b698-1f2deb4c0109","added_by":"auto","created_at":"2024-07-31 05:35:50","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":204616,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eChanges in the disease activity index and colon length of the irritable bowel syndrome models. \u003c/strong\u003e(A) The average disease activity index (DAI) comparison between the control and the acute model with weeks on the X-axis and DAI scores on the Y-axis. (B) DAI comparison between the control and the chronic model. (C) Comparison of average colon length among the control, the acute model, and the chronic models. Shortening of the colon is an indicator of inflammation and tissue damage. (D) Photographs of colons from the control, the acute model, and the chronic models, demonstrating differences in colon length and appearance.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-4680753/v1/72c4386a781640c5ba38241c.png"},{"id":61465033,"identity":"bf8c6b6d-abed-4f19-898b-236bc4edd929","added_by":"auto","created_at":"2024-07-31 05:35:56","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":179000,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eChanges in colon transit time of the irritable bowel syndrome models. \u003c/strong\u003e(A) Comparison of gastrointestinal transit time (GITT) between the control and the acute model. GITT was measured as the time taken for carmine red dye to travel through the gastrointestinal tract. (B) Comparison of bead expulsion test (BET) between the control and the acute model. BET measures the time taken for a bead inserted into the distal colon to be expelled. (C) Comparison of GITT between the control and the chronic model. (D) Comparison of BET between the control and the chronic model. (E) Representative images from closed-circuit television used to monitor GITT. Left image shows the time of carmine red administration (T\u003csub\u003e0\u003c/sub\u003e), and the right image shows the first appearance of carmine red-colored stool (indicated by red dots circle).\u003c/p\u003e\n\u003cp\u003eEach analytic value in graphs A-D is expressed as mean ± standard deviation.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-4680753/v1/9c2f56026a841307280b7215.png"},{"id":61465032,"identity":"fb5d19f7-bfd0-4137-95b4-3153f64401cf","added_by":"auto","created_at":"2024-07-31 05:35:52","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":225669,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003emRNA expression of genes encoding inflammatory cytokines and tight junction proteins in the proximal and the distal colons of the irritable bowel syndrome models. \u003c/strong\u003e(A–D) Mean mRNA expression values of IL-1β (A), IL-17 (B), TNF-α (C), and occludin (D) in the proximal colon of both models. In the acute model, elevated levels of IL-1β, IL-17, and TNF-α indicate increased inflammation, while decreased occludin suggests compromised intestinal barrier function. (E–H) Mean mRNA expression values of IL-1β\u003cem\u003e \u003c/em\u003e(E), IL-17 (F), TNF-α (G), and occludin (H) in the distal colon of both models.\u003c/p\u003e\n\u003cp\u003emRNA expression was quantified using the comparative Ct method with glyceraldehyde-3-phosphate dehydrogenase (GAPDH) as the internal control.\u003c/p\u003e\n\u003cp\u003eIL, interleukin; TNF, tumor necrosis factor.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-4680753/v1/d3d271560865fc4dd574cfe9.png"},{"id":61465028,"identity":"da102d0a-fcda-4beb-ab3d-bb82206047a4","added_by":"auto","created_at":"2024-07-31 05:35:50","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":238079,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eImmunohistochemistry and immunohistochemical staining of neuroinflammatory markers in the irritable bowel syndrome models. \u003c/strong\u003e(A, B)\u003cstrong\u003e \u003c/strong\u003eExpression of TRPV 1 (A) and TrkA (B) in both models. In the acute model, TRPV 1 and TrkA are quantitatively and meaningfully higher in immunopostive cells. (C) Immunochemical staining of TRPV 1 (upper panels) and TrkA (lower panels) in the lamina propria layer of the acute model compared to the control. Increased expression of these markers in the acute model suggests enhanced neuroinflammation and potential visceral hypersensitivity.\u003c/p\u003e\n\u003cp\u003eTRPV 1, transient receptor potential vanilloid 1; TrkA, tropomyosin receptor kinase A.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-4680753/v1/68f0cb63a7deadafb9fd8412.png"},{"id":61465027,"identity":"3240de07-3772-450c-8944-9aa0685e2b81","added_by":"auto","created_at":"2024-07-31 05:35:50","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":158563,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eComparison of the alpha diversity and beta diversity of the microbiome between the controls and the IBS model. \u003c/strong\u003e(A) Alpha diversity indices (Observed features, Chao1 index, Shannon's index, Simpson's index, and Pielou's evenness) comparing the microbiome diversity within individual samples between the control and the acute model considered as an IBS model. No significant differences were observed in alpha diversity. (B) Beta diversity analysis (Bray-Curtis dissimilarity and Unweighted UniFrac dissimilarity) comparing the microbiome composition between the control and the IBS model. Significant differences in beta diversity indicate distinct microbial communities between the two groups.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-4680753/v1/c3cf3946f55cb36c1ff3f5cb.png"},{"id":61465428,"identity":"5be18199-7f12-4a1f-ab77-18ee71b3ea9f","added_by":"auto","created_at":"2024-07-31 05:43:50","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":122137,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTaxonomy composition analysis between the controls and the IBS model. \u003c/strong\u003e(A)\u003cstrong\u003e \u003c/strong\u003eRelative abundance of the top 30 genera in the microbiome of the control and the acute model considered as an IBS model. (B) Genera with significantly different abundance between the control and IBS model. A higher abundance of genera such as \u003cem\u003eLachnospiraceae\u003c/em\u003e and \u003cem\u003eRuminococcaceae\u003c/em\u003e in the IBS model suggests their potential role in the disease’s pathophysiology.\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-4680753/v1/e5505fd8c9a0d8474dcb031c.png"},{"id":78689138,"identity":"a7e820d5-e5b8-4436-9c7b-004e8816d331","added_by":"auto","created_at":"2025-03-17 16:11:48","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2122175,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4680753/v1/35e72478-98c5-4fa8-ac65-e95b7a0715ae.pdf"},{"id":61465031,"identity":"d9271421-1bb4-4c35-9d36-f3868b665a5d","added_by":"auto","created_at":"2024-07-31 05:35:50","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":2242669,"visible":true,"origin":"","legend":"","description":"","filename":"3.SupplementaryInformationJeongetal240703.docx","url":"https://assets-eu.researchsquare.com/files/rs-4680753/v1/042371e5811e788fa2f778ad.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Establishment of Post-Inflammatory Irritable Bowel Syndrome Animal Model Following Acute Colitis Recovery","fulltext":[{"header":"Introduction","content":"\u003cp\u003eIrritable bowel syndrome (IBS) is a prevalent functional gastrointestinal disorder characterized by recurring abdominal pain associated with defecation or changes in bowel habits with no evidence of abnormalities in digestive organs.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e The prevalence of IBS has been estimated to exceed 10% of the global population,\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e underscoring its significant medical concern. IBS substantially affects the quality of life of patients and places a considerable burden on the healthcare system.\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e IBS is a multifactorial disease and the precise pathophysiology is unclear.\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e The pathogenesis of IBS has focused on abnormalities in visceral hypersensitivity, motility, brain-gut interaction, and psychosocial distress, and more recently, altered immune activation, changes of gut permeability and microbiome have been demonstrated in a subset of IBS patients.\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e Additionally, the influence of diet and nutritional components further contributes to the intricate dynamics of IBS.\u003c/p\u003e \u003cp\u003eResearch on developing and validating animal models based on IBS pathophysiology has gained interest for the effective management of IBS.\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e Various animal models have been developed to study IBS, among which the stress-induced chronic visceral pain model is the most commonly used. However, these models possess limitations in fully replicating the complexity of human IBS. Wang et al.\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e proposed a rodent model involving central stimulation induced by water avoidance stress, restraint stress, and neonatal-maternal separation. Additionally, Moloney et al.\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e described two pain models: early-life stress-induced visceral pain using a maternal separation stress model and adult stress-induced visceral pain using acute or chronic water avoidance stress. Although these IBS animal models have contributed to the understanding of psychosocial or life-threatening stress, there is a need for versatile methods that can effectively address the complexities of IBS modeling while avoiding complex experimental setups and equipment, and adhering to animal research ethics.\u003c/p\u003e \u003cp\u003eAnother IBS model was the post-infectious induced IBS model. Long et al.\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e investigated visceral hyperalgesia and colonic muscle hypercontractility in IBS mice models induced by acute or chronic \u003cem\u003eTrichinella spiralis\u003c/em\u003e infection. The activation of the immune system in colonic mucosa leads to immune cell infiltration and elevated levels of inflammatory cytokines, including interleukin (IL)-6, tumor necrosis factor (TNF)-α, and IL-1β in patients with IBS.\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e Similar to its application in inflammatory bowel disease (IBD), the post-inflammatory model emerges as a potential candidate for an IBS animal model, complementing those induced by psychological or life-threatening stress. Clinical symptoms overlap in patients with IBD who also present IBS-like symptoms.\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e The dextran sulfate sodium (DSS)-induced colitis mouse model has been widely used in IBD studies due to its ease of administration;\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e however, the exploration of experimental modeling specifically targeting low-grade inflammation related to IBS remains limited. Kodani et al.\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e analyzed gastrointestinal motility and macrophage/mast cell distribution during healing after induction of acute colitis with 2% DSS. However, similar to previous post-infectious IBS models, this study only analyzed changes following acute colitis, focusing on motility while not considering various other pathophysiological aspects of IBS, such as changes in visceral hypersensitivity, intestinal permeability, or microbial composition.\u003c/p\u003e \u003cp\u003eTherefore, in this study, we aimed to induce post-inflammatory IBS from acute severe colitis or chronic mild repeated colitis using DSS and assess the suitability of the model by examining low-grade inflammation induced gut dysmotility, altered permeability, increased visceral hypersensitivity and notable changes in microbial composition in a simple and efficient manner.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eExperimental Design\u003c/h2\u003e \u003cp\u003eSeven-week-old C57BL/6 male mice (Orient Bio Co., Ltd.\u0026reg;, Seongnam, Gyeonggi, Korea) were used in this study for IBS model induction. The mice were acclimated for 7 days at the Medical Research Center\u0026rsquo;s facility before experimentation. Mice were housed individually in standardized environmental conditions at 23\u0026thinsp;\u0026plusmn;\u0026thinsp;2\u0026deg;C with 50\u0026ndash;55% humidity and were allowed to feed food and drink \u003cem\u003ead libitum\u003c/em\u003e. The study protocol was approved by the Ethics Committee for Animal Research (EUM19-0456) and followed the ARRIVE 2.0 guidelines. Experimental procedures and results were conducted in accordance with regulations and guidelines.\u003c/p\u003e \u003cp\u003eThe mice were divided into two groups to induce the post-inflammatory IBS modeling: an acute severe colitis recovery IBS model (acute model) and a chronic mild repeated colitis IBS model (chronic model) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). For acute model, mice (n\u0026thinsp;=\u0026thinsp;10) were administered with 3% DSS (MP biochemical\u0026reg;, Irvine, CA, USA) for 5 days, followed by a 12-week recovery period. During the recovery period, mice were given free access to food and water. The traditional IBD model involved a chronic model in which mice (n\u0026thinsp;=\u0026thinsp;10) were orally administered with DSS for 5 days, followed by a recovery period of drinking water for the next 5 days, repeated for 3 cycles. To induce low-grade inflammation without causing gross mucosal damage, preliminary experiments were conducted to find an appropriate concentration of DSS, including 0.5%, 1.0%, and 1.5% for chronic models. Body weight changes, stool consistency, and gross bleeding were measured by the same observer every 7 days in the acute model and 3 days in the chronic model to assess disease activity, and the disease activity index (DAI) was calculated by adding the changes in body weight, stool consistency, and gross bleeding (Supplementary Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e).\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAfter completing the experiment in each model, all mice were euthanized through CO\u003csub\u003e2\u003c/sub\u003e asphyxiation after overnight fasting. After euthanasia, the entire colon was dissected from the cecum, and the total length was measured. Whole colon tissue was divided into proximal and distal sections, and then tissue from each section was split and analyzed by real-time polymerase chain reaction (RT-PCR), histopathology, and immunohistochemistry (IHC).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eAnalysis of Intestinal Transit Time\u003c/h2\u003e \u003cp\u003eWe used the gastrointestinal transit time (GITT) and the bead expulsion test to determine the intestinal transit time. For both techniques, we measured transit time before DSS administration and then every 4 weeks for the acute model and 30 days for the chronic model, respectively. Mice were housed individually to measure the GITT. A 6% solution of carmine red (natural red 4; Sigma Aldrich\u0026reg;, St. Louis, MO, USA), a non-absorbable dye, was administered through a 21-gauge gavage in 0.3 mL of 0.5% methylcellulose solution (Sigma Aldrich\u0026reg;). Following administration, mice were placed in a cage, the floors of which were lined with white paper to facilitate the carmine-red coloration of their feces. T\u003csub\u003e0\u003c/sub\u003e represented the time at which the carmine red solution was gavaged and the time it took for the expulsion of the first red fecal pellet was assessed.\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e In GITT measurements, closed-circuit television (CCTV) was employed as an auxiliary tool for more objective and accurate measurement.\u003c/p\u003e \u003cp\u003eIn the existing murine animal model, a bead expulsion test was a commonly used method to measure distal colonic transit time.\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e The distal colonic transit time was defined as the time between the bead insertion into the distal colon and its expulsion. Briefly, similar to previous studies, we dipped a single 2mm bead into the lubricating gel, gently inserted it, and measured the time to expulsion.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eRT-PCR analysis of Inflammatory Cytokines and Permeability Markers\u003c/h2\u003e \u003cp\u003eThe mRNA expression of inflammatory cytokines in the mice colon, including IL-1β, IL-6, IL-17, and TNF-α was measured. We assessed the mRNA expression of occludin, zonular occludens (ZO)-1, claudin-1, and claudin-4 using RT-PCR\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e to assess the expression of the tight junction proteins in the IBS model\u003c/p\u003e \u003cp\u003eRT-PCR was performed on proximal and distal colon sections. The separated colon tissue was immediately frozen at -70\u0026deg;C in a cryogenic freezer. Total RNA was isolated from colon tissue using the TRIzol reagent (Ambion\u0026reg;, Waltham, MA, USA). After adding chloroform (Sigma Aldrich\u0026reg;), the extracted total RNA was centrifuged at 12,000 rpm for 10 min at 4\u0026deg;C. The supernatants were centrifuged for 10 min at 12,000 rpm at 4\u0026deg;C with isopropanol (Sigma Aldrich\u0026reg;). After 75% ethanol wash, the pellet was solubilized with nuclease-free water and quantified using nano drops. RNA (2 \u0026micro;g) was reverse-transcribed in the mixture of oligo dT primers (0.5 \u0026micro;g), 200 units of Molony-Murine leukemia virus reverse transcriptase (Promega\u0026reg;, Fitchburg, WI, USA), 5x RT buffer, dNTPs (2 nM), and 25 units of RNasin ribonuclease inhibitor (Promega\u0026reg;) at 42 ℃ for 60 min. The RT-PCR was conducted on 7000 Real-time PCR systems (Applied Biosystems\u0026reg;, Waltham, MA, USA) with 2X Power SYBR Green PCR Master mix (Applied Biosystems\u0026reg;), 0.1 \u0026micro;g cDNA, and each primer set (Macrogen\u0026reg;, Seoul, Korea; Supplementary Table S2) over 40 cycles (95 ℃ for 15 s and 60 ℃ for 60 s) following pre-denature at 95 ℃ for 10 min. The relative expression of the target genes was assessed using the comparative Ct method, and glyceraldehyde-3-phosphate dehydrogenase was used as an internal control.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eHistopathological Analysis\u003c/h2\u003e \u003cp\u003eHistopathological examination was conducted by a single pathologist, and colon tissues were fixed in 10% formalin, followed by paraffin sectioning and hematoxylin-eosin (H\u0026amp;E) staining. Each colon tissue was stained with H\u0026amp;E and analyzed in three categories for histological evaluations: (i) inflammatory cell infiltrate, (ii) epithelial changes, and (iii) mucosal architecture. According to the criteria in histomorphological scores for intestinal inflammation in mouse models (Supplementary Table S3), each category was calculated with a score value ranging from 1 to 5.\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eImmunohistochemistry Analysis\u003c/h2\u003e \u003cp\u003eIHC analysis was performed, focusing on neuroinflammatory markers. Tissue samples were fixed in 4% paraformaldehyde in phosphate-buffered saline (pH 7.4), embedded in paraffin, and sectioned for IHC analysis. After deparaffinization and rehydration, antigen retrieval was performed by incubating the sections in citrate buffer (0.01 mmol/L, pH 6.0) and heating them in a microwave oven (720 W) for 15 min. Endogenous peroxidase was blocked by treating the sections in 0.3% hydrogen peroxide for 30 min at room temperature. Next, sections were incubated for 3 h at room temperature with specific antibodies: rabbit polyclonal transient receptor potential vanilloid 1 (TRPV 1) antibody (Invitrogen\u0026reg;, Waltham, USA), recombinant rabbit monoclonal tropomyosin receptor kinase A (TrkA) antibody (Invitrogen\u0026reg;), mouse monoclonal substance P antibody (Santa Cruz\u0026reg;, Dallas, TX, USA), rabbit monoclonal S-100 antibody (Leika\u0026reg;, Wetzlar, Germany), and mouse monoclonal neuron-specific enolase (NSE) antibody (Leika\u0026reg;) as visceral hypersensitivity markers. The sections were then incubated with horseradish peroxidase-conjugated goat anti-rabbit secondary antibodies for 30 min. The sections were then stained with 3,3-diaminobenzidine solution, followed by counterstaining with hematoxylin for nuclei labeling.\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e Immunopositive cells were counted using the Image J program (National Institutes of Health, Bethesda, MD, USA) in a 200 \u0026micro;m stretch of well-oriented entire colon epithelium sections at five randomly selective fields for each antibody. The average and standard deviation were subsequently calculated.\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eMicrobiome Analysis\u003c/h2\u003e \u003cp\u003eWe performed a microbiome analysis on the acute model selected as the IBS model based on comprehensive results. For microbiome analysis, intraluminal feces were collected from cecum of sacrificed mice and immediately frozen at -80 ℃. Microbial genomic DNA was extracted using QIAamp PowerFecal Pro DNA Kit (Qiagen\u0026reg;, Hilden, North Rhine-Westphalia, Germany), following the recommended protocols. The quality of all extracted bacterial genomic DNA was assessed using the Qubit 4 (ThermoFisher Scientific\u0026reg;, Waltham, MA, USA). The extracted mitochondrial DNA samples were stored at 4\u0026deg;C until further processing. The DNA sequencing library targeting the V3 and V4 hypervariable regions of 16S ribosomal RNA was constructed according to the sequencing library preparation protocol (Illumina\u0026reg;, San Diego, CA, USA) using specific universal primers (Illumina 16S forward 341F primer, 5'-TCGTCGGCAGCGTCAGATGTGTATAAGAGACAGCCTACGGGNGGCWGCAG \u0026minus;\u0026thinsp;3' and reverse 805R primer, 5'-GTCTCGTGGGCTCGGAGATGTGTATAAGAGACAG GACTACHVGGGTATCTAATCC-3').\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e PCR was carried out using KAPA HiFi HotStart ReadyMix (Kapa Biosystems\u0026reg;, Wilmington, MA, USA), followed by purification of the PCR product with AMPure XP beads (Beckman Coulter Genomics\u0026reg;, Brea, CA, USA). An additional PCR amplification was performed to introduce the Illumina adapter and multiplex indices using the Nextera XD Index (Illumina\u0026reg;). The final PCR products were purified once again using the AMPure XP beads. The prepared library was then sequenced using the Miseq system (Illumina\u0026reg;) with 300 bp paired-end reads.\u003c/p\u003e \u003cp\u003eThe gut microbiome data was analyzed using the QIIME2 pipeline plugin (2022.08).\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e Before implementing DADA2 (Divisive Amplicon Denoising Algorithm 2) in QIIME2, Figaro was used to determine optimal options based on sequence quality.\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eAmplicon sequence variants (ASVs) were obtained through the denoising step in the DADA2 algorithm. The ASVs were subjected to bacterial classification using a Na\u0026iuml;ve Bayes classifier based on targeted hypervariable reads extracted from the SILVA 138v 99% rRNA database to improve accuracy. Subsequently, various features annotated with Archaea, Eukaryotes, Mitochondria, or Chloroplasts were removed. The selected bacterial features were employed for the construction of a phylogeny tree using the align-to-tree-mafft-fasttree plugin, and taxonomy composition was determined. These features were rarefied at a specified depth and utilized for the analysis of alpha diversity, including Observed Features, Chao1 Index, Shannon's Index, Simpson's Index, and Pielou's Evenness, as well as beta diversity, encompassing Bray-Curtis and Unweighted UniFrac metrics.\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eStatistical Package for the Social Sciences (SPSS) program, version 25.0 software (SPSS Inc.\u0026reg;, Chicago, IL, USA) was used for all statistical analysis. The mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation values were used for each analysis. Comparisons of values between the models were tested using the nonparametric Kruskal\u0026ndash;Wallis test. Graphical representations were generated using GraphPad Prism software version 8 (GraphPad Software Inc.\u0026reg;, La Jolla, CA, USA). A \u003cem\u003eP\u003c/em\u003e-value of \u0026lt;\u0026thinsp;0.050 was considered statistically significant.\u003c/p\u003e \u003cp\u003eFor microbiome analysis, statistical significance in group comparisons for α-diversity and taxonomy composition was evaluated using the Mann-Whitney U-test (Wilcoxon Rank-sum test) in R through the 'ggpubr' package. To confirm the similarity between groups in distance matrices from β-diversity, principal coordinate analysis and permutational analysis of variance with 999 permutations were performed using the \u0026lsquo;Vegan\u0026rsquo; and \u0026lsquo;Adonis\u0026rsquo; packages in R. Additionally, linear discriminant analysis effect size (LEfSe) was calculated and features with a linear discriminant analysis score\u0026thinsp;\u0026ge;\u0026thinsp;2.0 were considered significant within each group.\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eChanges in the DAI of the IBS Models\u003c/h2\u003e \u003cp\u003eIn the acute model, the body weight decreased by 10.1\u0026thinsp;\u0026plusmn;\u0026thinsp;3.1% in the two weeks, then gradually increased and recovered in four weeks. The average DAI score was elevated at two weeks after DSS administration (6.8\u0026thinsp;\u0026plusmn;\u0026thinsp;1.1), and no disease activity was observed after four weeks (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIn the chronic model, body weight increased in the control, 0.5%, and 1.0% DSS groups but decreased by 3.2\u0026thinsp;\u0026plusmn;\u0026thinsp;7.6% in the 1.5% DSS group. Gross bleeding was observed only in the 1.0% DSS group (0.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6), whereas diarrhea or loose stool was observed in the 1.0%, 1.5%, and 0.5% DSS groups. The DAI scores were higher in the 1.0% and 1.5% DSS groups (5.3\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5 and 4.5\u0026thinsp;\u0026plusmn;\u0026thinsp;2.1, respectively) than in the 0.5% DSS group (1.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0; Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eChanges in Colon Length in the IBS Models\u003c/h2\u003e \u003cp\u003eThe colon length did not differ between the acute model and the control (99.5\u0026thinsp;\u0026plusmn;\u0026thinsp;7.9 mm vs. 103.0\u0026thinsp;\u0026plusmn;\u0026thinsp;9.6 mm, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.420). In the chronic model, the colon length in the 0.5% DSS group did not show significant differences from the control (92.9\u0026thinsp;\u0026plusmn;\u0026thinsp;6.6 mm vs. 103.0\u0026thinsp;\u0026plusmn;\u0026thinsp;9.6 mm, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.264); however, those in the 1.0% and 1.5% DSS groups (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.009 and \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.036) decreased significantly (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC, \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eChanges in Colon Transit Time in the IBS Models\u003c/h2\u003e \u003cp\u003eIn the acute model, GITT slowed compared to the control group up to 8 weeks after colitis induction but significantly accelerated by 12 weeks (146.9\u0026thinsp;\u0026plusmn;\u0026thinsp;40.2 min vs. 221.0\u0026thinsp;\u0026plusmn;\u0026thinsp;25.0 min, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001; Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). In the chronic model, no significant change in transit time was observed compared to the control after 30 days (157.0\u0026thinsp;\u0026plusmn;\u0026thinsp;33.2 min vs. 151.2\u0026thinsp;\u0026plusmn;\u0026thinsp;38.4 min, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.937; Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC). Moreover, no significant difference was observed in distal colon transit by bead expulsion test between the IBS models and the controls (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB, \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eExpression of Inflammatory Cytokine mRNAs in the IBS Models\u003c/h2\u003e \u003cp\u003eIn the proximal colon of the acute model, the mean mRNA expression of IL-1β and IL-17 were increased compared to those in the controls (2.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.7 vs. 1.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.034 for IL-1β; Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA, 2.5\u0026thinsp;\u0026plusmn;\u0026thinsp;2.9 vs. 1.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.7, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.041 for IL-17; Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB). In the distal colon of the acute model, the mean mRNA expression of IL-1β, IL-17, and TNF-α showed a significant increase compared to those in the controls (2.1\u0026thinsp;\u0026plusmn;\u0026thinsp;1.4 vs. 1.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.049 for IL-1β; Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eE, 2.9\u0026thinsp;\u0026plusmn;\u0026thinsp;3.3 vs. 1.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.028 for IL-17; Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eF, and 2.0\u0026thinsp;\u0026plusmn;\u0026thinsp;1.1 vs. 1.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.018 for TNF-α; Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eG).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIn the distal colon of the chronic model, a significant increase in the mean mRNA expression of IL-17 compared to that in the controls (2.3\u0026thinsp;\u0026plusmn;\u0026thinsp;1.7 vs. 1.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.026; Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eF). However, no remarkable increase in the expression of the inflammatory cytokines was observed in the proximal colon of the chronic model compared to that in the controls.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eExpression of Tight Junction Protein coding mRNAs in the IBS Models\u003c/h2\u003e \u003cp\u003eCompared to that in the controls, the expression of occludin mRNA in the proximal colon was only significantly decreased in the acute model (0.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4 vs. 1.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.041; Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD). In both models, the expression of ZO-1, claudin-1, and claudin-4 mRNAs did not differ from their expression in controls (Supplementary Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eA-F).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eHistopathological Evaluation in the IBS Models\u003c/h2\u003e \u003cp\u003eThe inflammatory severity and extent in colon tissue were evaluated using H\u0026amp;E stain (Supplementary Fig. S2). In both models, the colon tissue was observed to be grossly normal. The mild leukocyte infiltration was mainly observed in the distal colon of both models.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eExpression of Neuroinflammatory Markers in the IBS Models\u003c/h2\u003e \u003cp\u003eIn both the acute model and the control, the expression of TRPV 1 and TrkA in the colonic epithelium was observed. Scattered and weak IHC staining was observed on the basolateral membrane of epithelial cells, while inflammatory cells in the epithelium and lamina propria showed relatively strong TRPV 1 and TrkA expressions in the acute model. Quantitative analysis using the Image J program revealed increased immunopositivity in TRPV 1 and TrkA in the acute model compared to that in the controls (412.2\u0026thinsp;\u0026plusmn;\u0026thinsp;80.1 vs. 72.6\u0026thinsp;\u0026plusmn;\u0026thinsp;21.4, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.008 for TRPV 1 and 392.6\u0026thinsp;\u0026plusmn;\u0026thinsp;63.4 vs. 96.2\u0026thinsp;\u0026plusmn;\u0026thinsp;14.2, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.008 for TrkA) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA, \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB). However, immunopositivity of substance P, S100, and NSE was rarely detected in the acute model (Supplementary Fig. S3A, 3B, and 3C).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIn contrast, in the chronic model, none of the markers showed significant differences in expression compared to controls (64.6\u0026thinsp;\u0026plusmn;\u0026thinsp;13.6 vs. 48.4\u0026thinsp;\u0026plusmn;\u0026thinsp;10.8, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.095 for TRPV 1; 67.2\u0026thinsp;\u0026plusmn;\u0026thinsp;16.5 vs. 75.2\u0026thinsp;\u0026plusmn;\u0026thinsp;11.8, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.310 for TrkA) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA, \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB and Supplementary Fig. S3).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eComparative Analysis of Microbiomes in Control and the IBS model\u003c/h2\u003e \u003cp\u003eThe alpha-diversity analysis, encompassing Observed features, Chao1 index, Shannon's index, Simpson's index, and Pielou's evenness, did not reveal a significant difference in the level of diversity within individual samples between the acute model and the controls (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.050; Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA). However, the beta-diversity analysis between the two groups indicated notable differences in both Bray-Curtis dissimilarity (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001) and Unweighted UniFrac dissimilarity (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001), reflecting distinct microbial composition and dissimilarity (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB). At the genus level, 16 genera exhibited statistically significant differences between the two groups (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.050). LFfSe analysis revealed a higher abundance of \u003cem\u003eLachnospiraceae\u003c/em\u003e, \u003cem\u003eErysipelatoclostridium\u003c/em\u003e, \u003cem\u003e[Eubacterium] xylanophilum\u003c/em\u003e, \u003cem\u003eColidextribacter\u003c/em\u003e, \u003cem\u003eRuminococcaceae UBA1819\u003c/em\u003e, \u003cem\u003eMarvinbryantia\u003c/em\u003e, \u003cem\u003eAnaerotruncus\u003c/em\u003e, and \u003cem\u003eTuricibacter\u003c/em\u003e in the acute model compared to that in the control. Conversely, \u003cem\u003eClostridium sensu stricto 1\u003c/em\u003e, \u003cem\u003eRuminococcus\u003c/em\u003e, \u003cem\u003eBifidobacterium\u003c/em\u003e, \u003cem\u003eClostridia UCG-014\u003c/em\u003e, \u003cem\u003eAnaeroplasma\u003c/em\u003e, \u003cem\u003e[Eubacterium] fissicatena\u003c/em\u003e, and \u003cem\u003eRomboutstia\u003c/em\u003e exhibited a relatively higher abundance in the control group than that in the acute model (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e). These results showed no difference in the alpha diversity between the acute model and the control; however, noticeable changes in microbial composition were observed in the acute model.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, we successfully established a post-inflammatory IBS murine model using a recovery model after inducing acute severe colitis. The model was developed by inducing acute severe colitis with 3% DSS and allowing a recovery period of 12 weeks. However, chronic mild repeated colitis induced modeling was not demonstrated as a post-inflammatory IBS model. The criteria for a valid post-inflammatory IBS animal model include the absence of clinical signs of organic abnormalities (such as hematochezia, significant weight loss, or shortening of colon length), low-grade inflammatory changes without overt histological findings of colitis, and the presence of surrogate markers for IBS-related pathophysiology (such as gastrointestinal dysmotility or visceral hypersensitivity). Our post-inflammatory IBS murine model exhibited activation of low-grade inflammatory cytokines, decreased GITT, increased expression of neuroinflammatory markers, and microbial composition change without clinical and histological manifestations of organic colonic disorders.\u003c/p\u003e \u003cp\u003eIn comparison to various previous IBS animal models\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e, the stress-induced chronic visceral pain model has been commonly utilized. However, these models could pose ethical limitations due to the use of physical stressors like restraint, water avoidance, and neonatal-maternal separation in rodents.\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e Animal models of IBS with other mechanisms have been investigated, including several post-infectious IBS animal models caused by bacterial and parasitic infections such as \u003cem\u003eCampylobacter jejuni\u003c/em\u003e, \u003cem\u003eSalmonella enterica\u003c/em\u003e, or \u003cem\u003eTrichinella spiralis\u003c/em\u003e.\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e,\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e However, since post-infectious IBS is influenced by pathogens, there is a limitation that the symptoms in murine models induced by bacterial or parasitic pathogens may differ from those of actual human post-infectious IBS.\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e On the other hand, the representative post-inflammatory IBS model using trinitrobenzene sulfonic acid has the limitation of lacking a standardized protocol regarding dosage, concentration, and administration site.\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eTherefore, a new methodology of IBS animal modeling was required. Our approach aimed to establish a post-inflammatory IBS murine model by inducing low-grade inflammation using DSS, a method that is easily used for establishing IBS animal models.\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e,\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e Referring to the previous DSS-induced IBD murine model, we conducted experiments to induce low-grade inflammation by administering high concentrations of DSS for a short period or repeated low concentrations.\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e To evaluate bowel motility changes, we measured the change in intestinal transit time \u003cem\u003ein vivo\u003c/em\u003e.\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e In our IBS model, the GITT analysis using real-time CCTV showed that the transit time increased until 8 weeks after high-dose DSS administration and significantly decreased after 12 weeks compared to the controls. Similar to our study, a previous study reported changes in colonic motility following recovery from alterations in the mucosal immune system.\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e Our findings also demonstrated mild leukocyte infiltration in the lamina propria in both the acute and chronic models. Because various inflammatory cytokines were elevated in the acute model compared to those in the chronic model, we speculated that low-grade inflammation in the acute model may affect the enteric immune system, leading to the establishment of the IBS model. Additionally, we considered that the increase in IL-17 expression in the acute model, which can enhance intestinal muscle contractility, might affect colonic motility.\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eThe expression of the tight junction protein occludin decreased in the proximal colon of the acute model, whereas no notable differences were observed in the chronic model. Previous studies have also reported that intestinal permeability was related to tight junction proteins, and occludin plays a major role in IBS.\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e,\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e Co\u0026euml;ffier et al.\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e demonstrated that proteasome alterations enhance intestinal permeability due to decreased occludin expression in IBS. Furthermore, increased levels of IL-1β mRNA have been shown to reduce the occludin expression and increase intestinal permeability in a colitis mouse model.\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e Concordant with these studies; our study also demonstrates decreased occludin expression induced by IL-1β overexpression.\u003c/p\u003e \u003cp\u003eVisceral hypersensitivity is an important pathogenesis of IBS and can be induced by various pathophysiological abnormalities. To indirectly predict visceral hypersensitivity, we used IHC staining for several neuroinflammatory markers known to be associated with visceral hypersensitivity in previous studies. In the human IBS study, TRPV 1 expression was shown to be elevated in the mucosal nerve fibers and correlated with the abdominal pain score.\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e TrkA is a nerve growth factor that mediates nerve fiber growth and pain transmission.\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e In addition, substance P, S100 protein, and NSE were over-expressed in IBS patients.\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e The IHC staining results for these markers showed that TRPV 1 and TrkA immunopositivity was quantitatively higher only in the acute colitis model. Therefore, we could indirectly predict that our IBS model might have increased visceral hypersensitivity.\u003c/p\u003e \u003cp\u003eSeveral studies have posited that microbial alterations play a role in the pathogenesis of IBS. In our acute model, we observed an increase in the abundance of \u003cem\u003eLachnospiraceae\u003c/em\u003e and \u003cem\u003eRuminococcaceae\u003c/em\u003e, indicating differences in microbial composition and dissimilarity. Jeffery et al.\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e reported that \u003cem\u003eLachnospiraceae\u003c/em\u003e alters the function of the mucous barrier, and \u003cem\u003eRuminococcaceae\u003c/em\u003e produces abundant short-chain fatty acids associated with visceral hypersensitivity\u0026ndash;both these factors may contribute to the induction of IBS. While the specific gut microbiota groups influencing the etiology of IBS remain to be precisely elucidated, our model demonstrates the potential to serve as a novel IBS model compared to earlier research.\u003c/p\u003e \u003cp\u003eThe strength of our model is that it was constructed using a relatively simple method compared to previous animal IBS models. Additionally, we conducted \u003cem\u003ein vivo\u003c/em\u003e studies from various perspectives to evaluate the mechanism of the post-inflammatory IBS model induced by low-grade inflammation changes. Despite this strength, our models have certain limitations. We did not specifically address the potential impact of sex in each model, and our measurements focused on whole gut transit and distal colon transit rather than precise colon transit time. However, previous \u003cem\u003ein vivo\u003c/em\u003e studies of GITT in mice using magnetic resonance imaging showed high construct validity with the human study.\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e Another limitation is that we did not directly measure colorectal distension to predict visceral hypersensitivity. Instead, we used IHC staining for neuroinflammation markers to indirectly predict visceral hypersensitivity.\u003c/p\u003e \u003cp\u003eIn conclusion, the acute model induced the post-inflammatory IBS experimental model, demonstrating low-grade inflammation, gut dysmotility, changes in permeability, and increased visceral hypersensitivity with notable microbial composition changes. This experimental modeling holds promise for diverse IBS studies, allowing investigations into pathophysiological mechanisms and targeted therapies in the future.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analyzed in the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by a KSNM grant of the Korean Society of Neurogastroenterology and Motility for 2022.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eE.S.J., H.K.J.: research conceptualization, experimental methodology, experiment, data analysis, drafting of the manuscript;E.S.J., H.K.J., A.Y.L., Y.S.K.: review and editing of the manuscript; E.N.C.: pathologic analysis and review; K.E.Y, Y.S.K.: microbiome experiment and analysis. All authors reviewed the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eHoltmann, G. J., Ford, A. C. \u0026amp; Talley, N. J. Pathophysiology of irritable bowel syndrome. The lancet Gastroenterology \u0026amp; hepatology 1, 133\u0026ndash;146 (2016).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLembo, A. J. The clinical and economic burden of irritable bowel syndrome. Pract Gastroenterol 31, 3\u0026ndash;9 (2007).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDrossman, D. A. Functional gastrointestinal disorders: history, pathophysiology, clinical features, and Rome IV. Gastroenterology 150, 1262\u0026ndash;1279. e1262 (2016).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang, Y. \u003cem\u003eet al.\u003c/em\u003e Rodent model of irritable bowel syndrome. Int. J. Gastroenterol. Disord. Ther 4, 131 (2017).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMoloney, R. D., O'Mahony, S. M., Dinan, T. G. \u0026amp; Cryan, J. F. Stress-induced visceral pain: toward animal models of irritable-bowel syndrome and associated comorbidities. Front Psychiatry 6, 15 (2015). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org:10.3389/fpsyt.2015.00015\u003c/span\u003e\u003cspan address=\"https://doi.org:10.3389/fpsyt.2015.00015\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLong, Y., Liu, Y., Tong, J., Qian, W. \u0026amp; Hou, X. Effectiveness of trimebutine maleate on modulating intestinal hypercontractility in a mouse model of postinfectious irritable bowel syndrome. European Journal of Pharmacology 636, 159\u0026ndash;165 (2010). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org:https://doi.org/10.1016/j.ejphar.2010.03.037\u003c/span\u003e\u003cspan address=\"https://doi.org:10.1016/j.ejphar.2010.03.037\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLazaridis, N. \u0026amp; Germanidis, G. Current insights into the innate immune system dysfunction in irritable bowel syndrome. Annals of gastroenterology 31, 171 (2018).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHalpin, S. J. \u0026amp; Ford, A. C. Prevalence of Symptoms Meeting Criteria for Irritable Bowel Syndrome in Inflammatory Bowel Disease: Systematic Review and Meta-Analysis. Official journal of the American College of Gastroenterology | ACG 107, 1474\u0026ndash;1482 (2012). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org:10.1038/ajg.2012.260\u003c/span\u003e\u003cspan address=\"https://doi.org:10.1038/ajg.2012.260\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChassaing, B., Aitken, J. D., Malleshappa, M. \u0026amp; Vijay-Kumar, M. Dextran sulfate sodium (DSS)-induced colitis in mice. Curr Protoc Immunol 104, 15.25.11\u0026ndash;15.25.14 (2014). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org:10.1002/0471142735.im1525s104\u003c/span\u003e\u003cspan address=\"https://doi.org:10.1002/0471142735.im1525s104\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKodani, M. \u003cem\u003eet al.\u003c/em\u003e Association between gastrointestinal motility and macrophage/mast cell distribution in mice during the healing stage after DSS\u0026ndash;induced colitis. Molecular medicine reports 17, 8167\u0026ndash;8172 (2018).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIto, R. \u003cem\u003eet al.\u003c/em\u003e Interferon-gamma is causatively involved in experimental inflammatory bowel disease in mice. Clin Exp Immunol 146, 330\u0026ndash;338 (2006). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org:10.1111/j.1365-2249.2006.03214.x\u003c/span\u003e\u003cspan address=\"https://doi.org:10.1111/j.1365-2249.2006.03214.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi, Z. \u003cem\u003eet al.\u003c/em\u003e Essential roles of enteric neuronal serotonin in gastrointestinal motility and the development/survival of enteric dopaminergic neurons. Journal of Neuroscience 31, 8998\u0026ndash;9009 (2011).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKishi, K., Kamizaki, M., Kaji, N., Iino, S. \u0026amp; Hori, M. A close relationship between networks of interstitial cells of Cajal and gastrointestinal transit in vivo. Frontiers in Pharmacology 11, 587453 (2020).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTurner, J. R., Buschmann, M. M., Romero-Calvo, I., Sailer, A. \u0026amp; Shen, L. in \u003cem\u003eSeminars in cell \u0026amp; developmental biology.\u003c/em\u003e 204\u0026ndash;212 (Elsevier).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eErben, U. \u003cem\u003eet al.\u003c/em\u003e A guide to histomorphological evaluation of intestinal inflammation in mouse models. International journal of clinical and experimental pathology 7, 4557 (2014).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLuo, C. \u003cem\u003eet al.\u003c/em\u003e Upregulation of the transient receptor potential vanilloid 1 in colonic epithelium of patients with active inflammatory bowel disease. International journal of clinical and experimental pathology 10, 11335 (2017).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBukin, Y. S. \u003cem\u003eet al.\u003c/em\u003e The effect of 16S rRNA region choice on bacterial community metabarcoding results. Scientific Data 6, 1\u0026ndash;14 (2019).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBolyen, E. \u003cem\u003eet al.\u003c/em\u003e Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nature biotechnology 37, 852\u0026ndash;857 (2019).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCallahan, B. J. \u003cem\u003eet al.\u003c/em\u003e DADA2: High-resolution sample inference from Illumina amplicon data. Nature methods 13, 581\u0026ndash;583 (2016).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWeinstein, M. M., Prem, A., Jin, M., Tang, S. \u0026amp; Bhasin, J. M. FIGARO: An efficient and objective tool for optimizing microbiome rRNA gene trimming parameters. \u003cem\u003ebioRxiv\u003c/em\u003e, 610394 (2019).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChang, F., He, S. \u0026amp; Dang, C. Assisted selection of biomarkers by linear discriminant analysis effect size (LEfSe) in microbiome data. JoVE (Journal of Visualized Experiments), e61715 (2022).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGreenwood-Van Meerveld, B., Prusator, D. K. \u0026amp; Johnson, A. C. Animal models of gastrointestinal and liver diseases. Animal models of visceral pain: pathophysiology, translational relevance, and challenges. American Journal of Physiology-Gastrointestinal and Liver Physiology 308, G885-G903 (2015).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBeatty, J. K., Bhargava, A. \u0026amp; Buret, A. G. Post-infectious irritable bowel syndrome: mechanistic insights into chronic disturbances following enteric infection. World journal of gastroenterology: WJG 20, 3976 (2014).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eQin, H.-Y. \u003cem\u003eet al.\u003c/em\u003e Systematic review of animal models of post-infectious/post-inflammatory irritable bowel syndrome. Journal of gastroenterology 46, 164\u0026ndash;174 (2011).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePerše, M. \u0026amp; Cerar, A. Dextran sodium sulphate colitis mouse model: traps and tricks. Journal of Biomedicine and Biotechnology 2012 (2012).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKodani, M. \u003cem\u003eet al.\u003c/em\u003e Association between gastrointestinal motility and macrophage/mast cell distribution in mice during the healing stage after DSS\u0026ndash;induced colitis. Mol Med Rep 17, 8167\u0026ndash;8172 (2018). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org:10.3892/mmr.2018.8926\u003c/span\u003e\u003cspan address=\"https://doi.org:10.3892/mmr.2018.8926\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAndoh, A., Ogawa, A., Bamba, S. \u0026amp; Fujiyama, Y. Interaction between interleukin-17-producing CD4\u0026thinsp;+\u0026thinsp;T cells and colonic subepithelial myofibroblasts: what are they doing in mucosal inflammation? Journal of gastroenterology 42, 29\u0026ndash;33 (2007).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCo\u0026euml;ffier, M. \u003cem\u003eet al.\u003c/em\u003e Increased proteasome-mediated degradation of occludin in irritable bowel syndrome. Official journal of the American College of Gastroenterology| ACG 105, 1181\u0026ndash;1188 (2010).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRawat, M. \u003cem\u003eet al.\u003c/em\u003e IL1B increases intestinal tight junction permeability by up-regulation of MIR200C-3p, which degrades occludin mRNA. Gastroenterology 159, 1375\u0026ndash;1389 (2020).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAkbar, A. \u003cem\u003eet al.\u003c/em\u003e Increased capsaicin receptor TRPV1-expressing sensory fibres in irritable bowel syndrome and their correlation with abdominal pain. Gut 57, 923\u0026ndash;929 (2008).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJard\u0026iacute;, F., Fern\u0026aacute;ndez-Blanco, J. A., Mart\u0026iacute;nez, V. \u0026amp; Vergara, P. Plasticity of dorsal root ganglion neurons in a rat model of post-infectious gut dysfunction: potential implication of nerve growth factor. Scandinavian journal of gastroenterology 49, 1296\u0026ndash;1303 (2014).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJeffery, I. B., Quigley, E. M., \u0026Ouml;hman, L., Simr\u0026eacute;n, M. \u0026amp; O'Toole, P. W. The microbiota link to irritable bowel syndrome: an emerging story. Gut Microbes 3, 572\u0026ndash;576 (2012). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org:10.4161/gmic.21772\u003c/span\u003e\u003cspan address=\"https://doi.org:10.4161/gmic.21772\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchwarz, R., Kaspar, A., Seelig, J. \u0026amp; K\u0026uuml;nnecke, B. Gastrointestinal transit times in mice and humans measured with 27Al and 19F nuclear magnetic resonance. Magnetic Resonance in Medicine: An Official Journal of the International Society for Magnetic Resonance in Medicine 48, 255\u0026ndash;261 (2002).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Irritable bowel syndrome, Murine model, Dextran sulfate sodium, Low-grade inflammation, Dysmotility, Microbiome","lastPublishedDoi":"10.21203/rs.3.rs-4680753/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4680753/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIrritable bowel syndrome (IBS) is a prevalent disorder with an unclear pathophysiology. This study aimed to establish an experimental murine model of post-inflammatory IBS induced by acute severe colitis (acute model) or chronic mild repeated colitis (chronic model) to facilitate IBS analysis. The acute model was induced with 3% dextran sulfate sodium (DSS) for 5 days, followed by a 12-week recovery period. The chronic model involved administration of 0.5% DSS for 5 days, followed by a 5-day resting period, repeated thrice. We conducted comparative analyses to assess inflammation severity, intestinal motility, permeability, visceral hypersensitivity, and microbiome composition. In the acute model, mild leukocyte infiltration was observed, colonic transit time shortened at 12 weeks (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), occludin expression decreased (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.041), and inflammatory cytokines and transient receptor potential vanilloid 1 was upregulated in colonic mucosa (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.050). In the chronic model, only mild inflammatory changes were noted. Microbiota analysis in the acute model revealed differences in microbial abundance and compositions (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001). The acute model effectively induced a post-inflammatory IBS model, characterized by low-grade inflammation that causes gut dysmotility, alters permeability, and increases visceral hypersensitivity with notable microbial composition changes.\u003c/p\u003e","manuscriptTitle":"Establishment of Post-Inflammatory Irritable Bowel Syndrome Animal Model Following Acute Colitis Recovery","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-31 05:35:45","doi":"10.21203/rs.3.rs-4680753/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-10-29T05:07:22+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-10-28T14:08:00+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"310453862697802745179716229081296974642","date":"2024-10-24T07:26:19+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-09-06T16:53:29+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"203601905256446648665731742133859482037","date":"2024-08-26T01:45:59+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"111283125228053569101951238210195408832","date":"2024-08-25T10:39:41+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-07-23T09:50:17+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-07-23T09:35:10+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-07-12T16:10:32+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-07-08T08:37:47+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2024-07-03T13:29:02+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"eb91b343-7d88-4d96-8d96-c20c3dbbeda1","owner":[],"postedDate":"July 31st, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":35325160,"name":"Health sciences/Gastroenterology/Gastrointestinal diseases"},{"id":35325161,"name":"Health sciences/Gastroenterology/Gastrointestinal models"},{"id":35325162,"name":"Health sciences/Diseases/Gastrointestinal diseases/Functional gastrointestinal disorders"}],"tags":[],"updatedAt":"2025-03-17T16:06:18+00:00","versionOfRecord":{"articleIdentity":"rs-4680753","link":"https://doi.org/10.1038/s41598-025-88981-7","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2025-03-12 15:57:34","publishedOnDateReadable":"March 12th, 2025"},"versionCreatedAt":"2024-07-31 05:35:45","video":"","vorDoi":"10.1038/s41598-025-88981-7","vorDoiUrl":"https://doi.org/10.1038/s41598-025-88981-7","workflowStages":[]},"version":"v1","identity":"rs-4680753","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4680753","identity":"rs-4680753","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}