Development of a novel complex inflammatory bowel disease mouse model: Reproducing human inflammatory bowel disease etiologies in mice

Sun-Min Seo; Na-Won Kim; Eun-Seon Yoo; Ji-Hun Lee; Ah-Reum Kang; Han-Bi Jeong; Won-Yong Shim; Dong-Hyun Kim; Young-Jun Park; Kieun Bae; Kyong-Ah Yoon; Yang-Kyu Choi

doi:10.1371/journal.pone.0311310

. 2024 Nov 21;19(11):e0311310. doi: 10.1371/journal.pone.0311310

Development of a novel complex inflammatory bowel disease mouse model: Reproducing human inflammatory bowel disease etiologies in mice

Sun-Min Seo ¹, Na-Won Kim ¹, Eun-Seon Yoo ¹, Ji-Hun Lee ¹, Ah-Reum Kang ¹, Han-Bi Jeong ¹, Won-Yong Shim ¹, Dong-Hyun Kim ¹, Young-Jun Park ¹, Kieun Bae ², Kyong-Ah Yoon ², Yang-Kyu Choi ^1,^*

Editor: Pradeep Dudeja³

PMCID: PMC11581264 PMID: 39570897

Abstract

Inflammatory bowel disease (IBD), caused by environmental factors associated with the host’s genetic traits, is represented by Crohn’s disease and ulcerative colitis. Despite the increasing number of patients with IBD, the current treatment is limited to symptomatic therapy. A complex IBD model mimicking the human IBD etiology is required to overcome this limitation. Herein, we developed novel complex IBD models using interleukin 2 receptor subunit gamma (Il2rg)-deficient mice, high-fat diet, dextran sodium sulfate, and Citrobacter rodentium. The more IBD factors applied complexly, colon length shortened and inflammation worsened. The levels of pro-inflammatory cytokines increased with increased IBD factors. Anti-inflammatory cytokine decreased in all factors application but increased in Il2rg deficiency and Westernized diet combination. Additionally, the pro-inflammatory transcription factors and leaky intestinal epithelial marker were upregulated by a combination of IBD factors. Species diversity decreased with IBD factors. Phylogenetic diversity decreased as IBD factors were applied but increased with combined Il2rg deficiency and Westernized diet. The more IBD factors applied complexly, the more severe the dysbiosis. Finally, we developed a novel complex IBD model using various IBD factors. This model more closely mimic human IBD based on colonic inflammation and dysbiosis than the previous models. Based on these results, our novel complex IBD model could be a valuable tool for further IBD research.

1. Introduction

Inflammatory bowel disease (IBD), represented by Crohn’s disease (CD) and ulcerative colitis (UC) is a chronic inflammatory disease of the gastrointestinal tract. CD and UC are caused by environmental factors, such as a Westernized diet [1–3], changes in the intestinal flora [4, 5], and chemical stress [6, 7], depending on the host’s genetic traits [4, 5]. The prevalence of IBD has increased annually due to industrialization and overnutrition. Therefore, the incidence rate, previously high in the United States, Europe, and Oceania, shows an accelerating prevalence rate in Asia, South America, and Africa [8].

Despite the increasing number of patients with IBD and the social burden due to the westernization of emerging countries, only symptomatic treatment using 5-aminosalicylic acid, corticosteroids, immunosuppressants, anti-tumor necrosis factor-α (TNF-α) agents, and bowel resection has been used as treatment methods for IBD. However, immunosuppressants, anti-TNF-α agents, and bowel resection are burdensome for lifelong patients because of their side effects and invasive nature [9]. Since fecal microbiota transplantation (FMT) was first used to treat Clostridium difficile infection in humans, it has been studied as an alternative therapeutic strategy [10]. However, FMT is still limited to clinical trials for IBD treatment [11].

Research on fundamental IBD therapeutics and their etiology is ongoing to overcome these limitations, and these studies require animal models that mimic the pathogenesis of human IBD. Currently developed animal models that mimic human IBD etiology include diet-induced [12, 13], bacteria-induced [14–16], chemical-induced [7, 14, 17–19], and genetically engineered models [20, 21].

However, many IBD models so far have limitations such that they do not mimic the complex pathogenicity of IBD in humans but only fragmentarily mimic the human IBD etiology. We hypothesized that combining various IBD factors could create an IBD model that mimics the current complex pathogenicity of human IBD. Therefore, we used high-fat diet to mimic Westernized diet [2, 3]; Citrobacter rodentium, a human model of EHEC and EPEC, to mimic pathogenic bacterial infection [14]; Dextran sodium sulfate (DSS) to mimic chemical stress [2, 14]; and interleukin 2 receptor subunit gamma (Il2rg)-deficient mice, also known as the common gamma chain, to mimic genetic traits [22]. We tested a combination of these IBD factors in a mouse model to test this hypothesis.

2. Methods

2.1. Experimental design

Eight-week-old wild-type C57BL/6J mice and Il2rg-deficient mice, generated using the CRISPR/Cas9 genome editing system in a previous study [22], were divided into C57BL/6J wild-type mice (WT) (n = 12), Il2rg-deficient mice fed with normal-diet (ND) (n = 12), Il2rg-deficient mice fed with high-fat diet (HFD) (n = 12), and Il2rg-deficient mice treated with high-fat diet, C. rodentium, and DSS (HCD) (n = 13). Furthermore, mice were fed with a 60% kcal rodent diet (D12492, Research Diets Inc., New Brunswick, NJ, USA) or a normal rodent diet (Teklad 2018S, Inotiv, West Lafayette, IN, USA) ad libitum for 56 days (8 weeks). After the application of each diet, the WT, ND, and HFD groups were monitored for an additional 17 days. In the HCD group, after 56 days of 60% kcal rodent diet administration, 1.6 × 10⁸ CFU of C. rodentium (ATCC 51459, ATCC, Manassas, VA, USA) was suspended in Luria-Bertani broth and administered with single intragastric inoculation and 1% DSS (Dextran sodium sulfate salt, colitis grade, MP Biomedicals, Irvine, CA, USA) for 7 days, ad libitum. After administration, the HCD group was monitored for an additional 10 days (Fig 1). All groups of mice were observed daily. Mice were immediately euthanized if they experienced 20% body weight loss. One mouse in the ND group was euthanized due to reaching the humane endpoint criteria by malocclusion. The euthanized mouse in the ND group was excluded from the analysis. No animals died before meeting humane endpoint criteria. Environmental enrichment including wood chew block and pulp house (Woojung Bio, Republic of Korea) were provided to diminish distress. All procedures were performed by trained researchers and in accordance with the Konkuk University Institutional Animal Care and Use Committee (IACUC) and ARRIVE guidelines and regulations. The study was approved by Konkuk University IACUC (KU22048).

Fig 1 — Eight-week-old wild-type C57BL/6J and Il2rg-deficient mice were divided into C57BL/6J wild-type (WT) group (n = 12), Il2rg-deficient mice fed with normal diet (ND) group (n = 11), Il2rg-deficient mice fed with high-fat diet (HFD) group (n = 12), and Il2rg-deficient mice treated with high-fat diet, C. *rodentium*, and DSS (HCD) group (n = 13). Furthermore, a 60% kcal rodent diet or a normal rodent diet was fed to each group for 56 days (8 weeks). In the HCD group, 1.6 × 10⁸ CFU of C. *rodentium* was administered using single intragastric inoculation, and 1% of DSS was administered for 7 days, ad libitum. After administration, the HCD group was monitored for an additional 10 days. The WT, ND, and HFD groups were monitored for an additional 17 days after 56 days of diet application.

2.2. Histopathology

Whole colons were harvested from mice after euthanasia. Euthanasia was performed using CO₂ with a flow rate of 30% to 70% of chamber volume/min in compliance with AVMA guidelines. Each group of colons was trimmed using the Swiss roll technique, followed by fixation with 10% neutral-buffered formalin. After the routine processing and paraffin-embedded procedure, the tissues were cut into 4 um sections and stained with hematoxylin and eosin (H&E). The sections were evaluated using a BX53 light microscope (Olympus, Tokyo, Japan), and images were captured using a DP74 system (Olympus). The histopathological severity of each group of colons was scored using criteria modified from a previous study [23]. The modified histopathological criteria are presented in Table 1. The ratio of the inflamed area to the total colonic area in each group was also calculated. Histopathological analyses were performed independently on three separate researchers.

Table 1. Histopathological scoring criteria for IBD.

Parameter	Score	Criteria
Severity of inflammation	0	Rare inflammatory cells in the lamina propria
	1	Increased numbers of granulocytes in the lamina propria
	2	Confluence of inflammatory cells extending into the submucosa
	3	Transmural extension of the inflammatory infiltrate
Crypt damage	0	Intact crypts
	1	Loss of the basal one-third
	2	Loss of the basal two-thirds
	3	Entire crypt loss
Erosion	0	Absence of erosion
	1	1 to 3 foci of erosion
	2	4 to 6 foci of erosion
	3	Confluent or extensive erosion
Ulceration	0	Absence of ulceration
	1	1 to 3 foci of ulceration
	2	4 to 6 foci of ulceration
	3	Confluent or extensive ulceration

Open in a new tab

2.3. Myeloperoxidase assay

The supernatant obtained by homogenizing the colon tissue was measured for myeloperoxidase (MPO) using the myeloperoxidase activity assay kit (Colorimetric) (Ab105136, Abcam, Cambridge, UK) according to the manufacturer’s instructions. The results are shown as units per milligram of the weight of tissue.

2.4. Cytokine evaluation

The colon tissue was homogenized using FastPrep-24 5G (MP Biomedicals). After homogenization, total RNA was extracted using the MagListo^™ 5M Universal RNA Extraction Kit (Bioneer, Daejeon, Republic of Korea) and reverse-transcribed to cDNA using Maxime^™ RT PreMix (Oligo dT Primer, iNtRon Biotechnology, Gyeonggi, Republic of Korea). Quantitative real-time polymerase chain reaction (qPCR) was performed using AccuPower^® 2X GreenStar^™ qPCR Master Mix (Bioneer). The cycling procedure was as follows: pre-denaturation at 95 ºC for 5 min, denaturation at 95 ºC for 15 s, and annealing/extension at 60 ºC for 30 s. Forty cycles were performed using a CFX96 Touch Real-Time PCR Detection System (Bio-rad, Hercules, CA, USA). Target cytokines and specific primers used are listed in Table 2. To detect relative changes in mRNA levels of interferon gamma (IFN-γ), interleukin-1 beta (IL-1β), interleukin-6 (IL-6), interleukin-10 (IL-10), C-X-C motif chemokine ligand 10 (CXCL10), and tumor necrosis factor- α (TNF-α) cytokine mRNA levels of each sample were normalized using glyceraldehyde 3-phosphate dehydrogenase (GAPDH).

Table 2. Specific primers for the target cytokines.

1	GAPDH	F	5’- `AAC TTT GGC ATT GTG GAA GG` -3’
		R	5’- `ACA CAT TGG GGG TAG GAA CA` -3’
2	IFN-γ	F	5’`- TCA AGT GGC ATA GAT GTG GAA GAA` -3’
		R	5’- `TGG CTC TGC AGG ATT TTC ATG` -3’
3	Il-1β	F	5’- `TCG CTC AGG GTC ACA AGA AA` -3’
		R	5’- `CAT CAG AGG CAA GGA GGA AAA C` -3’
4	Il-6	F	5’- `ACA AGT CGG AGG CTT AAT TAC ACA T` -3’
		R	5’- `TTG CCA TTG CAC AAC TCT TTT C` -3’
5	Il-10	F	5’- `ACC TGG TAG AAG TGA TGC CCC AGG CA` -3’
		R	5’- `CTA TGC AGT TGA TGA AGA TGT CAA A` -3’
6	CXCL10	F	5’- `TTG TGC GAA AAG AAG TGC AG` -3’
		R	5’- `TAC AAA CAC AGC CTC CCA CA` -3’
7	TNF-α	F	5’- `AGG CTG CCC CGA CTA CGT` -3’
		R	5’- `GAC TTT CTC CTG GTA TGA GAT AGC AAA` -3’

Open in a new tab

2.5. Enzyme-linked immunosorbent assay (ELISA)

Enzyme-linked immunosorbent assay (ELISA) was performed to measure the levels of inflammatory and anti-inflammatory cytokines in each group of mice. The cytokines including interferon-gamma (IFN-γ), interleukin-1 beta (IL-1β), interleukin-6 (IL-6), interleukin-10 (IL-10), C-X-C motif chemokine ligand 10 (CXCL10), and tumor necrosis factor-α (TNF-α) were quantified using the Duoset ELISA kit (R&D systems, Minneapolis, MN, USA) following the manufacturer’s instructions. Serum from mice was collected and tested without dilution. Absorbance was measured using the SpectraMax microplate reader (Molecular Devices, San Jose, CA, USA).

2.6. Western blot

Proteins were extracted from the colon (5-10mg) using RIPA buffer (1X, Cell Signaling Technology, Beverly, MA, USA) supplemented with phosphatase inhibitor cocktail (1X, Cell signaling Technology), protease inhibitor (1X, Quartett, Berlin, Germany), dithiothreitol (2 mM, Thermo Scientific, Waltham, MA, USA), and phenylmethanesulfonyl fluoride (1 mM, Sigma-Aldrich, Brulington, MA, USA). Protein concentration was calculated using a Pierce™ BCA Protein Assay Kit (Thermo Scientific). Equal amounts of protein (10 ug per lane) were separated by SDS-polyacrylamide gel electrophoresis and transferred to Immobilon-P nitrocellulose membranes (Merck, Kenilworth, NJ, USA). The membranes were blocked with 5% skim milk in TBS with 1% Trixon X-100 (TBST) for 1 hour at room temperature and then incubated overnight at 4°C with the primary antibodies against β-actin (A1978, 1:5000; Sigma-Aldrich), NF-κB p65 (sc-8008, 1:1000; Santa Cruz Biotechnology, Santa Cruz, CA), and Claudin-2 (32–5600, 1:1000; Life Technologies, Carlsbad, CA, USA). Proteins were visualized using a horseradish peroxidase-conjugated secondary antibody and enhanced chemiluminescence reagent (Bio-Rad Laboratories). The intensities of the bands were visualized by using ImageQuant LAS 4000 (GE Healthcare, Little Chalfont, England) and Image Lab software (V 6.0.1, Bio-rad).

2.7. Extraction and sequencing of DNA

The samples used for microbiome analysis, the outer mucus of the colon, were stored at -80 ºC in a deep freezing condition. The samples were sent to LAS (Gimpo, Republic of Korea) for total DNA extraction, next-generation sequencing (NGS) library preparation, and sequencing. Dropsense96 (Trinean, Gent, Belgium) was used for quality control and accurate DNA quantification of each sample. After DNA quantification, NGS library preparation for the V3-V4 region was performed using the 16S Metagenomic Sequencing Library preparation (Illumina, San Diego, CA, USA). Quality control for the NGS library was conducted using Fragment Analyzer (Agilent Technologies, Santa Clara, CA, USA) and dsDNA 910 Reagent Kit, 35 bp–1,500 bp (Agilent Technologies). Sequencing was subsequently conducted using the MiSeq Sequencing System (Illumina) with 300 bp paired-end reads.

2.8. Biome analysis

Demultiplexed sequences were filtered by sequence quality, and a feature table was generated after chimeric reads were removed using the DADA2 plugin [24]. Naive Bayes classifiers pre-trained with reference database (Greengenes2 2022.10) [25, 26] were used to assign taxonomy to each sequence. Full analysis, including the determination of alpha and beta analyses, was performed using the QIIME2 program [27], and comparative analyses were performed using LEfSe [28]. Data visualization was conducted using Dokdo (1.16.0) [29].

2.9. Statistical analysis

Data are presented as mean ± standard error of the mean (SEM). Comparison between 4 groups (WT, ND, HFD, and HCD group) was performed using the Kruskal-Wallis test. The permutational multivariate analysis of variance (PERMANOVA) was performed for beta diversity analyses. All statistical analyses were performed using GraphPad Prism 9.5.1 (GraphPad Software Inc., San Diego, CA, USA). P<0.05 was considered statistically significant.

3. Results

3.1. Gross lesion and histopathological differences induced by the combination of IBD-affecting factors

Combinations of factors known to affect IBD have been used to reproduce the disease in mice, mimicking human IBD. The genetic factors were imitated using Il2rg-deficient mice generated by the CRISPR/CAS9 genome editing system in our previous study [22]. In addition, a high-fat diet, C. rodentium, and DSS were co-administered to mimic a Westernized diet and environmental factors. The C57BL/6J mice with a genetic background of Il2rg-deficient mice were used as a control group for comparison.

After 73 days of the experiment procedure, the colons were harvested, and their lengths were measured (Fig 2). Gross lesions and colon shortening were not observed in the WT and ND groups. However, macroscopic shortening was observed HFD and HCD groups. Colonic hypertrophy was observed in the HCD group (Fig 2A). The intestines were measured to confirm the difference in colon length between each group. The mean colon length was 8.38 cm, 8.42 cm, 7.35 cm, and 5.38 cm in the WT, ND, HFD, and HCD groups, respectively. There was no significant difference in colon length between the WT and ND groups. However, significant differences were observed between the WT and HCD (P<0.001), and ND and HCD (P<0.001) (Fig 2B).

Based on the gross lesion results, histopathological examination and scoring of the colon in each group were performed. Histopathological findings showed that inflammatory cell infiltration was absent in the WT and ND groups, similar to the gross lesions. However, unlike the WT and ND groups, the HFD group showed infiltration of inflammatory cells in the lamina propria. Moreover, in the HCD group, an increase in the number of inflammatory cells in the mucosa and submucosa, transmural inflammation, loss of epithelial crypts, and epithelial ulceration were observed (Fig 3A). Histopathological findings were scored based on the criteria listed in Table 1 to compare the pathological findings in each group. In contrast to the WT and ND groups, which had scores of 0, the mean values of the HFD and HCD groups were 0.67 and 4.50, respectively. The WT and ND groups showed a significant difference from the HCD group (P<0.01 and P<0.001, respectively) (Fig 3B). Also, the ratio of the inflamed area to the total area was calculated. The percentage of inflamed areas also showed similar results to the histopathological scoring in the colon. Those of the WT and ND groups were 0%; however, those of the HFD and HCD groups were 2.23% and 7.79%, respectively. Significant differences were observed between the WT and HCD groups and the ND and HCD groups (P<0.01) (Fig 3C). In addition, the colonic MPO activity, a specific biomarker for IBD, was remarkably higher in the HCD group, depending on the severity of inflammation. MPO activity of the WT, ND, and HFD groups were 0.75, 0.97, and 2.21 unit/mg, respectively. However, in the HCD group, MPO activity was 6.08 unit/mg. Significant differences were observed between the WT and HCD groups (P<0.001) and the ND and HCD groups (P<0.01) (Fig 3D).

Fig 3 — (A) Representative sections of H&E stained the colon of each group. Swiss rolls of whole colons (left: magnification x12.5) were magnified to assess levels of colitis (right: magnification x100); Inflammation (black star); transmural inflammation (white arrowhead); ulceration (black arrowhead). (B) The colon of each group was scored following the scoring criteria indicated in Table 1. (n = 5–6) (C) The ratio of the inflamed area to the total colonic area for each group. (n = 5–6) (D) Myeloperoxidase (MPO) activity in colon tissues. (n = 6–7). The data for each group is represented as the mean ± SEM. *P < 0.05; **P < 0.01; ***P < 0.001. (Kruskal-Wallis test).

3.2. Inflammatory and anti-inflammatory cytokine expression differed depending on the combination of IBD-affecting factors

Based on the gross lesions and histopathological differences between each group, pro-inflammatory and anti-inflammatory cytokines were analyzed to determine how these factors affect inflammation in the colon. mRNA expression levels of pro-inflammatory cytokines, including interferon-gamma (IFN-γ), interleukin-1 beta (Il-1β), interleukin 6 (Il-6), C-X-C motif chemokine ligand 10 (CXCL10), TNF-α, and mRNA expression level of anti-inflammatory cytokine interleukin 10 (Il-10) were analyzed from colon tissue.

Even though relative levels of IFN-γ increased as IBD occurred, no significant differences were observed between each group (Fig 4A). Relative levels of Il-1β also increased, depending on the IBD factor. The HCD group showed 1.44 times higher Il-1β levels than the WT group (P<0.01) (Fig 4B). The relative levels of Il-6 increased as IBD progressed. The ND group showed 0.66 times lower IL-6 levels than the WT group; however, no significant difference was observed. The HCD group showed 3.82 times higher Il-6 levels than the ND group (P<0.01) (Fig 4C). The relative levels of CXCL10 also increased as the IBD factor was applied. The HCD group showed 1.24 times higher CXCL10 levels than the WT group (P<0.05) (Fig 4E). Relative levels of TNF-α increased, depending on the IBD factor application. The HCD group showed 1.53 times higher TNF-α levels than the WT group (P<0.01). (Fig 4F). The relative levels of Il-10, an anti-inflammatory cytokine, were considerably higher in the HFD group and lower in the HCD group than those in the WT and ND groups. The HCD group showed 0.16 times lower Il-10 levels than the HFD group (P<0.001) (Fig 4D).

To assess the reliability of mRNA expression level results of inflammatory cytokines, the protein expression levels of the cytokines, including IFN-γ, Il-1β, Il-6, CXCL10, TNF-α, and Il-10 were also analyzed. Although IFN-γ did not show a significant difference in mRNA levels, protein levels of IFN-γ showed significant changes as IBD occurred. The HCD group showed 1.38 and 1.34 times higher than the WT and ND groups, respectively (P<0.05) (Fig 5A). The protein levels of Il-1β increased. The HCD group showed 1.89 times higher Il-1β levels than the WT group (P<0.05) (Fig 5B). The protein levels of Il-6 dramatically increased. The HCD group showed 3.86 and 3.88 times higher Il-6 levels than the WT and ND groups, respectively (P<0.01) (Fig 5C). The protein levels of CXCL10 also increased as the IBD factor was applied. The HCD group showed 1.47 and 1.35 times higher CXCL10 levels than the WT and ND groups, respectively (P<0.05) (Fig 5E). The protein expression of TNF-α increased in the HCD group. The HCD group showed 2.33 and 2.13 times higher TNF-α expression than the WT and ND groups (P<0.001, P<0.01) (Fig 5F). The protein levels of an anti-inflammatory cytokine, Il-10 showed the same trend as mRNA expression. The HCD group showed 1.88 times lower Il-10 levels than the HFD group (P<0.01) (Fig 5D).

Fig 5 — protein levels of pro-inflammatory and anti-inflammatory cytokines, including IFN-γ (A), Il-1β (B), Il-6 (C), Il-10 (D), CXCL10 (E), and TNF-α (F), were quantified from the serum of each group of mice. Each level of cytokines was measured through ELISA. The data for each group is represented as the mean ± SEM. (n = 6–7) *P < 0.05; **P < 0.01; ***P < 0.001. (Kruskal-Wallis test).

3.3. Combination of IBD-affecting factors exacerbate inflammation and loosen the intestinal barrier

Based on the histopathological changes between each group, NF-κB and Claudin-2 were analyzed. First, the NF-κB, a ubiquitous transcription factor activated in inflammatory status, was increased when inflammation worsened. The HCD group showed 1.76 times higher levels than the WT group (P<0.05) (Fig 6C). Second, Claudin-2, the tight junction marker that indicates the leakage in the intestinal barrier, was also increased in the same trend as NF-κB. The HCD group showed 2.95 times higher levels than the WT group (P<0.01) (Fig 6D).

Fig 6 — Representative images of NF-κB p65 (A) and Claudin-2 (B) expression in the colon by western blot analysis. The relative densities of NF-κB p65 (C) and Claudin-2 (D) were calculated relative to β-actin expression. The data for each group is represented as the mean ± SEM. (n = 6–7) *P < 0.05; **P < 0.01. (Kruskal-Wallis test).

3.4. Changes in the gut microbiota due to factors affecting IBD

As a combination of genetic factors, Westernized diet, and other environmental factors imitate IBD in humans, we investigated whether these combinations also affect the gut microbiota. Based on a previous study in which the outer mucus layer of the colon had more abundant microbiota than the inner mucus layer [30], the colon was opened longitudinally and sampled aseptically. Each outer mucus sample was sequenced and analyzed for the 16s rRNA (V3-V4) hypervariable region.

Alpha diversity, including the Shannon and Faith’s phylogenetic diversity (Faith-PD) indexes, was performed to identify the diversity in each group that varied with the IBD factors. The ND, HFD, and HCD groups showed lower Shannon index than the WT group. The HCD group showed significantly lower values than those in the other groups, and the HFD and ND groups showed significantly lower values than those in the WT group (P<0.01) (Fig 7A). The WT and ND groups showed similar values in the Faith-PD index, which considers phylogenetic distance. However, the HFD group showed higher values, and the HCD group showed lower values than those in the WT and ND groups. The HCD group showed significantly lower values than those in the WT, ND, and HFD groups (P<0.05, P<0.01, and P<0.01, respectively). However, the HFD group showed significantly higher values than the ND group (P<0.05) (Fig 7B). Based on Bray–Curtis dissimilarity, beta diversity was analyzed by drawing PCoA plots in 2D (Fig 7C) and the 3D (Fig 7D). Regarding Bray–Curtis dissimilarity, significant differences in distance were observed between all groups (P<0.001) (Fig 7C and 7D).

Fig 7 — Comparison of the colonic mucus bacterial community between groups. (A) Shannon index of each group; (B) Faith-PD index of each group; (C) Bray–Curtis distance of each group, 2D; (D) Bray–Curtis distance of each group, 3D. Data of quantitative analyses are represented as the mean ± SEM. (n = 6–7) *P < 0.05; **P < 0.01. (Alpha diversity: Kruskal–Wallis test; Beta diversity: PERMANOVA).

In the bar plot based on relative abundance at the phylum level (L2), the main phyla were Bacteroidetes and Firmicutes, followed by Proteobacteria, Deferribacterota, Verrucomicrobiota, Desulfobacterota, Actinobacteriota, Patescibacteria, Cyanobacteria, Fusobacteriota, Chloroflexota, Deinococcus, Bdellovibrionota, and Planctomycetota (Fig 8A). Based on previous studies on the correlation between IBD and changes in the ratio of Firmicutes to Bacteroidetes [31, 32]. The ratio of the Firmicutese/Bacteriodetes (F/B ratio) were present in the WT (113.25), ND (122.27), HFD (271.80), and HCD groups (81.93). F/B ratio significantly increased in the HFD group than HCD group (P<0.01) (Fig 8B). Differentially abundant operational taxonomic units (OTU) between each group were identified using linear discriminant analysis Effect Size (LEfSe). Among the OTUs with a linear discriminant analysis (LDA) score of ≥3.0, a heat map was generated by selecting a family associated with IBD. In total, 10 families were selected: Ruminococcaceae, Muribaculaceae, Bifidobacteriaceae, Lactobacillaceae, Erysipelotrichaceae, Oscillospiraceae, and Akkermansiaceae, which are known to be decreased in IBD conditions, and Enterobacteriaceae, Bacteroidaceae, and Enterococcaceae, which are known to be increased in IBD conditions. After analyzing these families for each group, a heatmap was drawn for the six observations. First, the relative abundance of Muribaculaceae and Bifidobacteriaceae gradually decreased as factors known to affect IBD were applied. Second, the relative abundance of Enterobacteriaceae and Bacteroidaceae increased as factors known to affect IBD were applied. Third, in all groups except the WT group, the relative abundances of Ruminococcaceae and Lactobacillaceae decreased, which are factors known to affect IBD. In the WT group, the relative abundances of Ruminococcaceae and Lactobacillaceae decreased. Fourth, in all groups except the WT group, the relative abundance of Enterococcacea increased as factors known to affect IBD were applied. The relative abundance of Enterococcaceae increased in the WT group. Fifth, the relative abundances of Erysipelotrichaceae and Oscillospiraceae were lower in the HCD group than in the other groups but higher in the HFD group than in the other groups. Sixth, the relative abundance of Akkermansiaceae was lower in the HCD group than in the ND group. In contrast to the distribution in the ND and HCD groups, it was rarely present in the WT group and was only a minority in the HFD group compared with the ND and HCD groups (Fig 8C).

Fig 8 — Relative abundance analysis of the colonic mucus bacterial community between groups. (A) Bar plot of the relative abundance at the phylum level of each group; (B) Firmicutes/Bacteriodetes (F/B) ratio between 4 different groups; (C) Heatmap of abundance variation of 10 selected common bacterial taxa in colonic mucus of each group. The relative abundance of selected taxa is based on LEfSe, in which the LDA score is >3.0. Black represents less abundance, red represents intermediate abundance, and white represents most abundance. Data from quantitative analyses are represented as the mean ± SEM. (n = 6–7) *P < 0.05; **P < 0.01; ***P < 0.001. (Kruskal-Wallis test).

4. Discussion

Since UC, and CD first reported in the early 1900s [33, 34], IBD has emerged as a severe threat to public health in modern society. Fundamental research and updates on therapeutic guidelines are active to reduce its global public health burden [9, 35]. A complex interaction of multiple factors influences the development of human IBD. However, current animal models of IBD often focus on specific factors, which limits their ability to fully understand the pathogenesis of IBD and their application in therapeutic research. For instance, genetic models of IBD in animals typically study the direct effect of a single gene, while in humans, disease risk is rarely associated with the complete loss of function of a single gene or protein [36, 37]. The limitation of chemically induced IBD models is inducing self-limiting inflammation rather than a chronic phase of inflammation, which mimics human pathogenesis [38]. Another example, diet-induced IBD models, have limitations in that models couldn’t cause IBD alone but must be applied together with other factors [12]. Novel animal models mimicking the complex pathogenesis of IBD in humans are required to overcome these limitations. However, no models that complexly mimic the etiology of human IBD have been developed yet. This study aimed to mimic the complex pathogenicity of human IBD combining various IBD factors in mice. Our results provide evidence that this novel complex IBD model reproduces human IBD and overcomes the limitations of the previous IBD models.

The severity of inflammation increased with the combination of IBD factors. As more factors were added to the mouse model, inflammation worsened and the colon shortened. Although Il2rg-deficient mice did not show pathological findings alone, mild inflammation in the HFD group was localized to the mucus layer, and the HCD group showed transmural inflammation and epithelial ulceration. Transmural inflammation and ulceration are the representative characteristics consistent with CD, the chronic IBD of the human [39]. These findings suggest that the limitation of the chemical-induced models, self-limiting inflammation, has been overcome due to a combination of IBD factors. Also, IBD is exacerbated through the combined application of IBD factors rather than focusing on the genetically modified model and its effects on the gene, suggesting that the limitations of the existing genetic model were overcome. Moreover, a key indicator of neutrophil infiltration in IBD, MPO was dramatically increased in the colon of the HCD group. This result is consistent with the previous study, which reported markedly increasing MPO levels in active IBD patients [40].

Cytokines, transcription factor, and tight junction protein associated with inflammation changed depending on the combination of IBD factors. Similar to the histopathological finding, the pro-inflammatory cytokines IFN-γ, Il-1β, Il-6, TNF-α, and CXCL-10 increased with the complex application of the IBD factor. TNF-α, a cytokine crucial in IBD both CD and UC, promotes the production of inflammatory cytokines and induces the death of intestinal epithelial cells [41]. Like TNF-α, the expression of Il-1β, and CXCL10 also increases in IBD conditions [42, 43]. IFN-γ, which plays a major role in CD pathogenesis [44], did not show significant differences in tissue mRNA level but in serum protein level. These conflicting results between mRNA and protein are consistent with previous studies suggesting that due to a synthesis delay between mRNA and protein [45]. Anti-inflammatory cytokines secreted from T cells, Il-10, appeared at lower levels in the HCD group and higher levels in the HFD group. The results from the HFD and HCD groups were consistent with previous studies showing that the Il-10 level was associated with worsening or resolving the disease [46]. Based on these results, it can be inferred that the HFD group with the application of chemical stress and dysbiosis, can cause the disease to progress from a self-limiting nature to a chronic form. Notably, the level of Il-6 remained low depending on the common gamma chain deletion. A direct correlation between Il-6 and the common gamma chain has not been revealed; however, previous studies show that Il-6 cooperates with common gamma chain-related cytokines, such as Il-2, Il-7, and Il-15, for T-cell activation [47]. Based on this previous study, it was deduced that Il-6 downregulation results from the absence of the common gamma chain. NF-κB, known to be upregulated in CD and UC, is a transcription factor involved in inflammatory and immune responses. After NF-κB activation by the pro-inflammatory mediator including IFN-γ, it activates transcription of various genes such as Il-1, Il-6, TNF-α, and CXCL-10 [48]. Another important marker, claudin-2 is a marker of tight junctions that indicates the permeability of the intestinal barrier. In both CD and UC, Claudin-2 is upregulated and exacerbates inflammation by increasing intestinal bacterial permeation [49, 50]. Upregulation of NF-κB and claudin-2 confirmed in the HCD group. This result indicates that the application of complex IBD. These pro- and anti-inflammatory cytokine, transcription factor, and tight junction protein patterns show that the combination of complex IBD factors successfully imitates human IBD pathogenesis.

Alterations in the gut microbiota appear to depend on a combination of IBD factors. Regarding alpha diversity, genetic factors did not cause phylogenetic differences but did cause differences in species diversity. The HFD group did not show a significant difference in species diversity compared with the ND group but showed significantly increased biodiversity in phylogenetic differences. This result is consistent with previous studies showing that ingesting HFD changes the gut microbiota of mice, regardless of whether the mice develop obesity [51]. However, despite being fed the same high-fat diet as the HFD group, the HCD group showed deprived biodiversity in both species and phylogenetic diversities compared with all other groups. Based on previous studies showing that dysbiosis occurred after administering DSS to healthy mice [52], we inferred that the combined administration of DSS and C. rodentium might lower alpha diversity. In addition, the beta diversity of the WT, ND, HFD, and HCD groups differed significantly. These results may be attributable to various IBD factors. In the relative abundance analysis, dysbiosis was identified through an imbalance between Firmicutes and Bacteroidetes. In our results, the HFD group showed high F/B ratio, whereas the HCD group showed low F/B ratio. These results correspond with those of previous studies, which stated that high F/B ratio indicated obesity condition and low F/B ratio indicated IBD condition [32]. Based on the relative abundance analysis results, Ruminococcaceae, Muribaculaceae, Bifidobacteriaceae, Lactobacillaceae, Erysipelotrichaceae, Oscillospiraceae, and Akkermansiaceae were the dominant families under healthy conditions, and Enterobacteriaceae, Bacteroidaceae, and Enterococcaceae were the dominant families under IBD conditions. This result is consistent with previous studies showing that Ruminococcaceae, Bifidobacteriaceae, Erysipelotrichaceae, Oscillospiraceae, and Akkermansiaceae were more abundant in healthy individuals, and Enterobacteriaceae, Bacteroidaceae, and Enterococcaceae were more abundant in patients with CD and UC [53–60]. In the HFD group, the levels of Akkermansiaceae and Erysipelotrichaceae were markedly lower and higher, respectively. Erysipelotrichaceae decreased in severe IBD conditions and increased with HFD application. These results are consistent with studies that Erysipelotrichaceae decreased in UC patients [61] and increased in obese conditions compared to healthy controls [62]. Additionally, the result for Akkermansiaceae is consistent with previous findings showing that the number of this family decreased in obese conditions [63]. Muribaculaceae, which are more abundant in mice than in other species, are dramatically reduced in mouse IBD models [64, 65]. Humans are the species known to have the highest levels of Muribaculaceae after mice, but research on patients with IBD is still ongoing. The evaluation of Lactobacillaceae is conflicting. Contrary to our findings that Lactobacillaceae are depleted when IBD factors are applied, Lactobacillaceae are reported to increase in patients with CD and UC [53, 55–58]. However, other studies that correspond to our results have shown that Lactobacillaceae are beneficial bacteria and can be a potential treatment for IBD [66, 67]. Rumincoccaceae, Lactobacillaceae, and Akkermansiaceae were lower in the WT group than in the Il2rg-deficient group, and Enterococcaceae were higher in the WT group than in the Il2rg-deficient group. These results are contrary to our expectations. These results, despite sufficient acclimation, are thought to be due to genetic differences [68]. Little research has been conducted on the correlation between common gamma chain deficiency and the levels of Ruminococcaceae, Lactobacillaceae, Akkermansiaceae, and Enterococcaceae. Therefore, further studies are required to determine these correlations.

This study’s data demonstrated that novel complex IBD models that mimic human IBD pathogenesis developed successfully. Despite developing several animal models for IBD therapeutic and pathogenesis research, current animal models have limitations in imitating the complex IBD pathogenesis. Our study revealed that animal models combining genetic traits and environmental factors, such as a Westernized diet, bacteria, and chemical stress, successfully mimic human IBD, especially CD, regarding chronic colitis and microbiota dysbiosis more closely than current models. In particular, this study demonstrated that the limitations of the existing IBD model were overcome by improving the current IBD model into a novel complex IBD model. Our novel complex IBD models could be valuable tools for IBD research, including the development of new therapeutic strategies and the elucidation of complex IBD pathogenesis.

Supporting information

S1 Raw image. Uncropped images of blot presented in Fig 6A & 6B.

(PDF)

pone.0311310.s001.pdf^{(521.6KB, pdf)}

Data Availability

All relevant data are within the manuscript.

Funding Statement

This work was supported by the Bio & Medical Technology Development Program of the National Research Foundation (NRF) funded by the Korea government (MSIT) (Nos. 2020R1A2C2005898 and 2021M3H9A1097269) and the Konkuk University Researcher Fund in 2023. the funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

References

1.Lewis JD, Abreu MT. Diet as a Trigger or Therapy for Inflammatory Bowel Diseases. Gastroenterology. 2017. Feb;152(2):398–414.e6. doi: 10.1053/j.gastro.2016.10.019 [DOI] [PubMed] [Google Scholar]
2.Cheng L, Jin H, Qiang Y, Wu S, Yan C, Han M, et al. High fat diet exacerbates dextran sulfate sodium induced colitis through disturbing mucosal dendritic cell homeostasis. Int Immunopharmacol. 2016. Nov;40:1–10. doi: 10.1016/j.intimp.2016.08.018 [DOI] [PubMed] [Google Scholar]
3.Sugihara K, Kamada N. Diet-Microbiota Interactions in Inflammatory Bowel Disease. Nutrients. 2021. May 1;13(5):1533. doi: 10.3390/nu13051533 [DOI] [PMC free article] [PubMed] [Google Scholar]
4.Ananthakrishnan AN, Bernstein CN, Iliopoulos D, Macpherson A, Neurath MF, Ali RAR, et al. Environmental triggers in IBD: a review of progress and evidence. Nat Rev Gastroenterol Hepatol. 2018. Jan;15(1):39–49. doi: 10.1038/nrgastro.2017.136 [DOI] [PubMed] [Google Scholar]
5.Mentella MC, Scaldaferri F, Pizzoferrato M, Gasbarrini A, Miggiano GAD. Nutrition, IBD and Gut Microbiota: A Review. Nutrients. 2020. Mar 29;12(4):944. doi: 10.3390/nu12040944 [DOI] [PMC free article] [PubMed] [Google Scholar]
6.Sanmarco LM, Chao CC, Wang YC, Kenison JE, Li Z, Rone JM, et al. Identification of environmental factors that promote intestinal inflammation. Nature. 2022. Nov;611(7937):801–809. doi: 10.1038/s41586-022-05308-6 [DOI] [PMC free article] [PubMed] [Google Scholar]
7.Kim JJ, Shajib MS, Manocha MM, Khan WI. Investigating intestinal inflammation in DSS-induced model of IBD. J Vis Exp. 2012. Feb 1;(60):3678. doi: 10.3791/3678 [DOI] [PMC free article] [PubMed] [Google Scholar]
8.Ng SC, Shi HY, Hamidi N, Underwood FE, Tang W, Benchimol EI, et al. Worldwide incidence and prevalence of inflammatory bowel disease in the 21st century: a systematic review of population-based studies. Lancet. 2017. Dec 23;390(10114):2769–2778. doi: 10.1016/S0140-6736(17)32448-0 [DOI] [PubMed] [Google Scholar]
9.Lamb CA, Kennedy NA, Raine T, Hendy PA, Smith PJ, Limdi JK, et al. British Society of Gastroenterology consensus guidelines on the management of inflammatory bowel disease in adults. Gut. 2019. Dec;68(Suppl 3):s1–s106. doi: 10.1136/gutjnl-2019-318484 [DOI] [PMC free article] [PubMed] [Google Scholar]
10.van Nood E, Vrieze A, Nieuwdorp M, Fuentes S, Zoetendal EG, de Vos WM, et al. Duodenal infusion of donor feces for recurrent Clostridium difficile. N Engl J Med. 2013. Jan 31;368(5):407–15. [DOI] [PubMed] [Google Scholar]
11.Caldeira LF, Borba HH, Tonin FS, Wiens A, Fernandez-Llimos F, Pontarolo R, et al. Fecal microbiota transplantation in inflammatory bowel disease patients: A systematic review and meta-analysis. PLoS One. 2020. Sep 18;15(9):e0238910. doi: 10.1371/journal.pone.0238910 [DOI] [PMC free article] [PubMed] [Google Scholar]
12.Shon WJ, Jung MH, Kim Y, Kang GH, Choi EY, Shin DM, et al. Sugar-sweetened beverages exacerbate high-fat diet-induced inflammatory bowel disease by altering the gut microbiome. J Nutr Biochem. 2023. Mar;113:109254. doi: 10.1016/j.jnutbio.2022.109254 [DOI] [PubMed] [Google Scholar]
13.Shon WJ, Song JW, Oh SH, Lee KH, Seong H, You HJ, et al. Gut taste receptor type 1 member 3 is an intrinsic regulator of Western diet-induced intestinal inflammation. BMC Med. 2023. Apr 28;21(1):165. doi: 10.1186/s12916-023-02848-0 [DOI] [PMC free article] [PubMed] [Google Scholar]
14.Park JI, Seo SM, Park JH, Jeon HY, Kim JY, Ryu SH, et al. A murine colitis model developed using a combination of dextran sulfate sodium and Citrobacter rodentium. J Microbiol. 2018. Apr;56(4):272–279. [DOI] [PMC free article] [PubMed] [Google Scholar]
15.Grassl GA, Valdez Y, Bergstrom KS, Vallance BA, Finlay BB. Chronic enteric salmonella infection in mice leads to severe and persistent intestinal fibrosis. Gastroenterology. 2008. Mar;134(3):768–80. doi: 10.1053/j.gastro.2007.12.043 [DOI] [PubMed] [Google Scholar]
16.Higgins LM, Frankel G, Douce G, Dougan G, MacDonald TT. Citrobacter rodentium infection in mice elicits a mucosal Th1 cytokine response and lesions similar to those in murine inflammatory bowel disease. Infect Immun. 1999. Jun;67(6):3031–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
17.Dieleman LA, Ridwan BU, Tennyson GS, Beagley KW, Bucy RP, Elson CO, et al. Dextran sulfate sodium-induced colitis occurs in severe combined immunodeficient mice. Gastroenterology. 1994. Dec;107(6):1643–52. doi: 10.1016/0016-5085(94)90803-6 [DOI] [PubMed] [Google Scholar]
18.Arita M, Yoshida M, Hong S, Tjonahen E, Glickman JN, Petasis NA, et al. Resolvin E1, an endogenous lipid mediator derived from omega-3 eicosapentaenoic acid, protects against 2,4,6-trinitrobenzene sulfonic acid-induced colitis. Proc Natl Acad Sci U S A. 2005. May 24;102(21):7671–6. doi: 10.1073/pnas.0409271102 [DOI] [PMC free article] [PubMed] [Google Scholar]
19.Boirivant M, Fuss IJ, Chu A, Strober W. Oxazolone colitis: A murine model of T helper cell type 2 colitis treatable with antibodies to interleukin 4. J Exp Med. 1998. Nov 16;188(10):1929–39. doi: 10.1084/jem.188.10.1929 [DOI] [PMC free article] [PubMed] [Google Scholar]
20.Mombaerts P, Mizoguchi E, Grusby MJ, Glimcher LH, Bhan AK, Tonegawa S, et al. Spontaneous development of inflammatory bowel disease in T cell receptor mutant mice. Cell. 1993. Oct 22;75(2):274–82. doi: 10.1016/0092-8674(93)80069-q [DOI] [PubMed] [Google Scholar]
21.Kühn R, Löhler J, Rennick D, Rajewsky K, Müller W. Interleukin-10-deficient mice develop chronic enterocolitis. Cell. 1993. Oct 22;75(2):263–74. doi: 10.1016/0092-8674(93)80068-p [DOI] [PubMed] [Google Scholar]
22.Lee JH, Park JH, Nam TW, Seo SM, Kim JY, Lee HK, et al. Differences between immunodeficient mice generated by classical gene targeting and CRISPR/Cas9-mediated gene knockout. Transgenic Res. 2018. Jun;27(3):241–251. doi: 10.1007/s11248-018-0069-y [DOI] [PMC free article] [PubMed] [Google Scholar]
23.Laroui H, Ingersoll SA, Liu HC, Baker MT, Ayyadurai S, Charania MA, et al. Dextran sodium sulfate (DSS) induces colitis in mice by forming nano-lipocomplexes with medium-chain-length fatty acids in the colon. PLoS One. 2012;7(3):e32084. doi: 10.1371/journal.pone.0032084 [DOI] [PMC free article] [PubMed] [Google Scholar]
24.Callahan BJ, McMurdie PJ, Rosen MJ, Han AW, Johnson AJ, Holmes SP, et al. DADA2: High-resolution sample inference from Illumina amplicon data. Nat Methods. 2016. Jul;13(7):581–3. doi: 10.1038/nmeth.3869 [DOI] [PMC free article] [PubMed] [Google Scholar]
25.Segata N, Izard J, Waldron L, Gevers D, Miropolsky L, Garrett WS, et al. Metagenomic biomarker discovery and explanation. Genome Biol. 2011. Jun 24;12(6):R60. doi: 10.1186/gb-2011-12-6-r60 [DOI] [PMC free article] [PubMed] [Google Scholar]
26.McDonald D, Jiang Y, Balaban M, Cantrell K, Zhu Q, Gonzalez A, et al. Greengenes2 enables a shared data universe for microbiome studies. BioRxiv [Preprint]. 2023. bioRxiv 520774. https://www.biorxiv.org/content/10.1101/2022.12.19.520774v2. [Google Scholar]
27.Bolyen E, Rideout JR, Dillon MR, Bokulich NA, Abnet CC, Al-Ghalith GA, et al. Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nat Biotechnol. 2019. Aug;37(8):852–857. doi: 10.1038/s41587-019-0209-9 [DOI] [PMC free article] [PubMed] [Google Scholar]
28.Bokulich NA, Kaehler BD, Rideout JR, Dillon M, Bolyen E, Knight R, et al. Optimizing taxonomic classification of marker-gene amplicon sequences with QIIME 2’s q2-feature-classifier plugin. Microbiome. 2018. May 17;6(1):90. doi: 10.1186/s40168-018-0470-z [DOI] [PMC free article] [PubMed] [Google Scholar]
29.Park, J. Y. et al. Do Different Samples From Pregnant Women and Their Neonates Share the Common Microbiome: A Prospective Cohort Study. Research Square [Preprint]. 2021 Research Square. https://www.researchsquare.com/article/rs-1062191/v1.
30.Johansson ME, Phillipson M, Petersson J, Velcich A, Holm L, Hansson GC, et al. The inner of the two Muc2 mucin-dependent mucus layers in colon is devoid of bacteria. Proc Natl Acad Sci U S A. 2008. Sep 30;105(39):15064–9. doi: 10.1073/pnas.0803124105 [DOI] [PMC free article] [PubMed] [Google Scholar]
31.Sokol H, Seksik P, Furet JP, Firmesse O, Nion-Larmurier I, Beaugerie L, et al. Low counts of Faecalibacterium prausnitzii in colitis microbiota. Inflamm Bowel Dis. 2009. Aug;15(8):1183–9. [DOI] [PubMed] [Google Scholar]
32.Stojanov S, Berlec A, Štrukelj B. The Influence of Probiotics on the Firmicutes/Bacteroidetes Ratio in the Treatment of Obesity and Inflammatory Bowel disease. Microorganisms. 2020. Nov 1;8(11):1715. doi: 10.3390/microorganisms8111715 [DOI] [PMC free article] [PubMed] [Google Scholar]
33.Allchin WH. A Discussion on "Ulcerative Colitis.": Introductory Address. Proc R Soc Med. 1909;2(Med Sect):59–75. [PMC free article] [PubMed] [Google Scholar]
34.Crohn BB, Ginzburg L, Oppenheimer GD. Regional ileitis: a pathologic and clinical entity. JAMA. 1932;99(16):1323–1329. [Google Scholar]
35.Kucharzik T, Ellul P, Greuter T, Rahier JF, Verstockt B, Abreu C, et al. ECCO Guidelines on the Prevention, Diagnosis, and Management of Infections in Inflammatory Bowel Disease. J Crohns Colitis. 2021. Jun 22;15(6):879–913. doi: 10.1093/ecco-jcc/jjab052 [DOI] [PubMed] [Google Scholar]
36.Baydi Z, Limami Y, Khalki L, Zaid N, Naya A, Mtairag EM, et al. An Update of Research Animal Models of Inflammatory Bowel Disease. ScientificWorldJournal. 2021. Dec 13;2021:7479540. doi: 10.1155/2021/7479540 [DOI] [PMC free article] [PubMed] [Google Scholar]
37.Katsandegwaza B, Horsnell W, Smith K. Inflammatory Bowel Disease: A Review of Pre-Clinical Murine Models of Human Disease. Int J Mol Sci. 2022. Aug 19;23(16):9344. doi: 10.3390/ijms23169344 [DOI] [PMC free article] [PubMed] [Google Scholar]
38.Lee CH, Koh SJ, Radi ZA, Habtezion A. Animal models of inflammatory bowel disease: novel experiments for revealing pathogenesis of colitis, fibrosis, and colitis-associated colon cancer. Intest Res. 2023. Jul;21(3):295–305. doi: 10.5217/ir.2023.00029 [DOI] [PMC free article] [PubMed] [Google Scholar]
39.Mills SC, von Roon AC, Tekkis PP, Orchard TR. Crohn’s disease. BMJ Clin Evid. 2011. Apr 27;2011:0416. [PMC free article] [PubMed] [Google Scholar]
40.Saiki T Myeloperoxidase concentrations in the stool as a new parameter of inflammatory bowel disease. Kurume Med J. 1998. 45;69–73. doi: 10.2739/kurumemedj.45.69 [DOI] [PubMed] [Google Scholar]
41.Günther C, Martini E, Wittkopf N, Amann K, Weigmann B, Neumann H, et al. Caspase-8 regulates TNF-α-induced epithelial necroptosis and terminal ileitis. Nature. 2011. Sep 14;477(7364):335–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
42.McAlindon ME, Hawkey CJ, Mahida YR. Expression of interleukin 1 beta and interleukin 1 beta converting enzyme by intestinal macrophages in health and inflammatory bowel disease. Gut. 1998. Feb;42(2):214–9. doi: 10.1136/gut.42.2.214 [DOI] [PMC free article] [PubMed] [Google Scholar]
43.Ostvik AE, Granlund AV, Bugge M, Nilsen NJ, Torp SH, Waldum HL, et al. Enhanced expression of CXCL10 in inflammatory bowel disease: potential role of mucosal Toll-like receptor 3 stimulation. Inflamm Bowel Dis. 2013. Feb;19(2):265–74. doi: 10.1002/ibd.23034 [DOI] [PubMed] [Google Scholar]
44.Langer V, Vivi E, Regensburger D, Winkler TH, Waldner MJ, Rath T, et al. IFN-γ drives inflammatory bowel disease pathogenesis through VE-cadherin-directed vascular barrier disruption. J Clin Invest. 2019. Nov;129(11):4691–4707. [DOI] [PMC free article] [PubMed] [Google Scholar]
45.Liu Y, Beyer A, Aebersold R. On the Dependency of Cellular Protein Levels on mRNA Abundance. Cell. 2016. Apr;165(3):535–50. doi: 10.1016/j.cell.2016.03.014 [DOI] [PubMed] [Google Scholar]
46.Asseman C, Mauze S, Leach MW, Coffman RL, Powrie F. An essential role for interleukin 10 in the function of regulatory T cells that inhibit intestinal inflammation. J Exp Med. 1999. Oct;190(7):995–1004. doi: 10.1084/jem.190.7.995 [DOI] [PMC free article] [PubMed] [Google Scholar]
47.Lin JX, Leonard WJ. The Common Cytokine Receptor γ Chain Family of Cytokines. Cold Spring Harb Perspect Biol. 2018. Sep;10(9):a028449. [DOI] [PMC free article] [PubMed] [Google Scholar]
48.Liu T, Zhang L, Joo D, Sun SC. NF-κB signaling in inflammation. Signal Transduct Target Ther. 2017;2:17023–. [DOI] [PMC free article] [PubMed] [Google Scholar]
49.Luettig J, Rosenthal R, Barmeyer C, Schulzke JD. Claudin-2 as a mediator of leaky gut barrier during intestinal inflammation. Tissue Barriers. 2015. Apr;3(1–2):e977176. doi: 10.4161/21688370.2014.977176 [DOI] [PMC free article] [PubMed] [Google Scholar]
50.Landy J, Ronde E, English N, Clark SK, Hart AL, Knight SC, et al. Tight junctions in inflammatory bowel diseases and inflammatory bowel disease associated colorectal cancer. World J Gastroenterol. 2016. Mar;22(11):3117–26. doi: 10.3748/wjg.v22.i11.3117 [DOI] [PMC free article] [PubMed] [Google Scholar]
51.Xiao L, Sonne SB, Feng Q, Chen N, Xia Z, Li X, et al. High-fat feeding rather than obesity drives taxonomical and functional changes in the gut microbiota in mice. Microbiome. 2017. Apr 8;5(1):43. doi: 10.1186/s40168-017-0258-6 [DOI] [PMC free article] [PubMed] [Google Scholar]
52.Zhang Q, Wu Y, Wang J, Wu G, Long W, Xue Z, et al. Accelerated dysbiosis of gut microbiota during aggravation of DSS-induced colitis by a butyrate-producing bacterium. Sci Rep. 2016. Jun 6;6:27572. doi: 10.1038/srep27572 [DOI] [PMC free article] [PubMed] [Google Scholar]
53.Pascal V, Pozuelo M, Borruel N, Casellas F, Campos D, Santiago A, et al. A microbial signature for Crohn’s disease. Gut. 2017. May;66(5):813–822. doi: 10.1136/gutjnl-2016-313235 [DOI] [PMC free article] [PubMed] [Google Scholar]
54.Halfvarson J, Brislawn CJ, Lamendella R, Vázquez-Baeza Y, Walters WA, Bramer LM, et al. Dynamics of the human gut microbiome in inflammatory bowel disease. Nat Microbiol. 2017. Feb 13;2:17004. doi: 10.1038/nmicrobiol.2017.4 [DOI] [PMC free article] [PubMed] [Google Scholar]
55.Lewis JD, Chen EZ, Baldassano RN, Otley AR, Griffiths AM, Lee D, et al. Inflammation, Antibiotics, and Diet as Environmental Stressors of the Gut Microbiome in Pediatric Crohn’s Disease. Cell Host Microbe. 2015. Oct 14;18(4):489–500. doi: 10.1016/j.chom.2015.09.008 [DOI] [PMC free article] [PubMed] [Google Scholar]
56.Imhann F, Vich Vila A, Bonder MJ, Fu J, Gevers D, Visschedijk MC, et al. Interplay of host genetics and gut microbiota underlying the onset and clinical presentation of inflammatory bowel disease. Gut. 2018. Jan;67(1):108–119. doi: 10.1136/gutjnl-2016-312135 [DOI] [PMC free article] [PubMed] [Google Scholar]
57.Moustafa A, Li W, Anderson EL, Wong EHM, Dulai PS, Sandborn WJ, et al. Genetic risk, dysbiosis, and treatment stratification using host genome and gut microbiome in inflammatory bowel disease. Clin Transl Gastroenterol. 2018. Jan 18;9(1):e132. doi: 10.1038/ctg.2017.58 [DOI] [PMC free article] [PubMed] [Google Scholar]
58.Franzosa EA, Sirota-Madi A, Avila-Pacheco J, Fornelos N, Haiser HJ, Reinker S, et al. Gut microbiome structure and metabolic activity in inflammatory bowel disease. Nat Microbiol. 2019. Feb;4(2):293–305. doi: 10.1038/s41564-018-0306-4 [DOI] [PMC free article] [PubMed] [Google Scholar]
59.Papa E, Docktor M, Smillie C, Weber S, Preheim SP, Gevers D, et al. Non-invasive mapping of the gastrointestinal microbiota identifies children with inflammatory bowel disease. PLoS One. 2012;7(6):e39242. doi: 10.1371/journal.pone.0039242 [DOI] [PMC free article] [PubMed] [Google Scholar]
60.Vich Vila A, Imhann F, Collij V, Jankipersadsing SA, Gurry T, Mujagic Z, et al. Gut microbiota composition and functional changes in inflammatory bowel disease and irritable bowel syndrome. Sci Transl Med. 2018. Dec 19;10(472):eaap8914. doi: 10.1126/scitranslmed.aap8914 [DOI] [PubMed] [Google Scholar]
61.Alam MT, Amos GCA, Murphy ARJ, Murch S, Wellington EMH, Arasaradnam RP. Microbial imbalance in inflammatory bowel disease patients at different taxonomic levels. Gut Pathog. 2020. Jan;12:1. doi: 10.1186/s13099-019-0341-6 [DOI] [PMC free article] [PubMed] [Google Scholar]
62.Kaakoush NO. Insights into the Role of Erysipelotrichaceae in the Human Host. Front Cell Infect Microbiol. 2015. Nov 20;5:84. doi: 10.3389/fcimb.2015.00084 [DOI] [PMC free article] [PubMed] [Google Scholar]
63.Everard A, Belzer C, Geurts L, Ouwerkerk JP, Druart C, Bindels LB, et al. Cross-talk between Akkermansia muciniphila and intestinal epithelium controls diet-induced obesity. Proc Natl Acad Sci U S A. 2013. May 28;110(22):9066–71. [DOI] [PMC free article] [PubMed] [Google Scholar]
64.Chang CS, Liao YC, Huang CT, Lin CM, Cheung CHY, Ruan JW, et al. Identification of a gut microbiota member that ameliorates DSS-induced colitis in intestinal barrier enhanced Dusp6-deficient mice. Cell Rep. 2021. Nov 23;37(8):110016. doi: 10.1016/j.celrep.2021.110016 [DOI] [PubMed] [Google Scholar]
65.Lagkouvardos I, Lesker TR, Hitch TCA, Gálvez EJC, Smit N, Neuhaus K, et al. Sequence and cultivation study of Muribaculaceae reveals novel species, host preference, and functional potential of this yet undescribed family. Microbiome. 2019. Feb 19;7(1):28. doi: 10.1186/s40168-019-0637-2 [DOI] [PMC free article] [PubMed] [Google Scholar]
66.Wang H, Zhou C, Huang J, Kuai X, Shao X. The potential therapeutic role of Lactobacillus reuteri for treatment of inflammatory bowel disease. Am J Transl Res. 2020. May 15;12(5):1569–1583. [PMC free article] [PubMed] [Google Scholar]
67.Huynh U, Zastrow ML. Metallobiology of Lactobacillaceae in the gut microbiome. J Inorg Biochem. 2023. Jan;238:112023. [DOI] [PMC free article] [PubMed] [Google Scholar]
68.Korach-Rechtman H, Freilich S, Gerassy-Vainberg S, Buhnik-Rosenblau K, Danin-Poleg Y, Bar H, et al. Murine Genetic Background Has a Stronger Impact on the Composition of the Gut Microbiota than Maternal Inoculation or Exposure to Unlike Exogenous Microbiota. Appl Environ Microbiol. 2019. Aug; 85(18):e00826–19. doi: 10.1128/AEM.00826-19 [DOI] [PMC free article] [PubMed] [Google Scholar]

PLoS One. doi: 10.1371/journal.pone.0311310.r001

Decision Letter 0

Pradeep Dudeja

8 Mar 2024

PONE-D-24-05316Development of novel complex inflammatory bowel disease mouse models: reproducing various human inflammatory bowel disease etiologies in micePLOS ONE

Dear Dr. Choi,

The major concerns remain about the lack of appropriate statistical analysis, failure to outline the limitations in previous models and how those have been overcome in the authors models. In addition, poor presentation of results, figures as well as grammatical errors further dampen the enthusiasm. Authors need to address the concerns of both the reviewers in a point by point manner.

Please submit your revised manuscript by Apr 22 2024 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.
An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols.

We look forward to receiving your revised manuscript.

Kind regards,

Pradeep Dudeja

Academic Editor

PLOS ONE

Journal Requirements:

When submitting your revision, we need you to address these additional requirements.

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at

https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and

https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf

2. Thank you for stating the following financial disclosure:

"This work was supported by the Bio & Medical Technology Development Program of the National Research Foundation (NRF) funded by the Korea government (MSIT) (Nos. 2020R1A2C2005898 and 2021M3H9A1097269) and the Konkuk University Researcher Fund in 2023."

Please state what role the funders took in the study. If the funders had no role, please state: "The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript."

If this statement is not correct you must amend it as needed.

Please include this amended Role of Funder statement in your cover letter; we will change the online submission form on your behalf.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Partly

Reviewer #2: No

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: No

**********

3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: No

**********

4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: No

Reviewer #2: Yes

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: The goal of this paper is to develop complex models that mimic IBD in humans more closely than currently available models. This is a descriptive paper focusing on some observations and does not delve into possible mechanisms.

The authors are requested to address the following comments and provide clarifications.

1. How many new models have been developed? Two? HFD and HCD? State this in the title.

2. Throughout the text authors make generalized statements without providing specifics. This should be avoided. For example, they consistently state that present models have limitations and while they provide references, they do not elaborate on what are the specific limitations. If the presented models are better, they need to specifically state how it overcomes the limitations of other models and give pertinent details of the other models.

3. Line 153-154: What happens if WT animals are fed a HFD? Do they develop any signs of inflammation as the Il2rg deficient mice?

4. Line 264: Unclear what is meant by 6 types – the six observations?

5. Line 310-312: Are there no other models that show these characteristics of inflammation? What makes the present model unique?

6. Line 315; When the authors state “gradually increased …” did they perform a time course to measure the increase in cytokine expression?

7. Line 317-318: If interferon gamma did not increase as anticipated, how do the authors reconcile this as being a good model for IBD.

8. Line 324-325: How do the authors reconcile the increase in IL-10 in the HFD group with the latter being a model for IBD (MC). IF this is information in Ref 51, it should be explained better.

9. Line 331-332: Do the authors conclude that HCD mimics CD and HFD mimics MC based strictly on PCR results of cytokine expression?

10. Line 347-350: The statements made on high vs low levels are difficult to follow with the date shown in Figure 4. For example while the figure shows low Firmicutes in HCD, it does not necessarily show high Bacteroidetes (the levels in HCD and ND are comparable.

11. Line 359-360: If Erysipelotrichaceae is high in the HFD group, then how does it reconcile with the previous sentence which states that these species are abundant in healthy individuals. Please clarify.

12. Line 375: A stronger argument with more convincing comparisons to other models and data are needed to support this conclusion.

13. Line 381-382, the authors state the HCD model is good for the study of human CD and UC and yet the discussion on the data does not provide evidence on the connection to UC.

Figures: The practice of embedding the figure legends in the text is not common and therefore a bit difficult to follow. The maximal details should be provided in the methods and those in the legend and figure should reflect the highlights. For example, the methods do not state how DSS was administered, but it is only stated in the figure 1.

All figure legends should state the “n” values even if they are the same for each experiment.

Figure 1: The methods should clearly reflect what was done. Lines 62-90 were confusing to this reviewer. It could be interpreted as 56+17 = 73 days (which seems to be the case based on the figure) or as 56days on ND +56days on diet +17 days = 129 days. As written in this and previous page it could be either. Is “0” day, the day of birth or are they 8 weeks old at that stage. If the former, when were the animals weaned from their dams?

Line 153-154 states that figure 1 shows “genetic factors were imitated….” This reviewer could not find that information in the figure. Please explain.

Figure 4: As done for figure 2 and 3, please indicate the cytokine being measured in the y-axes; it is difficult to follow if one has to refer back to the text.

Figure 6: Please label Y-axes in panels B and C, as stated for Figure 4.

Editorial: The paper should be carefully reviewed for editorial and grammatical inconsistencies. A few examples are provided and this list is not complete

line 43, should read “… Clostridium difficile infections…”;

line 65, the expansion of HCD should be provided when it is first used here;

Line 94-97: the sentence is repeated;

line 103: What is meant by “….performed independently on three individuals” – samples from three animals were analyzed or does it mean that the histopathological scoring and analyses (double blind) were conducted by three separate researchers?

Line 303: Do the authors mean altered bacterial environment (including composition) when they state “bacteria”?

Reviewer #2: In this study, the authors have developed the mouse model of IBD using various human IBD etiologies. However, many major concerns need to be addressed.

Major points:

• A change in the myeloperoxidase enzyme activity must support the change in the colon length.

• A complete picture of the Swiss roll must be provided along with the magnified inserts. The scale bar must be included in the picture.

• What does the bar diagram Fig 2B indicating the histopathological scoring indicate?

• The Fig2C bar diagram showing HFD and HCD standard deviation (SD) is very high. With this high SD, having a statistical significance in what is depicted is unrealistic. Therefore, statistics analysis must be revisited.

• To evaluate the reliability of the newly established IBD model, several parameters of key anti-inflammatory activity must be assessed. These include LI-6, IL-1B, TNF-alpha, and CXCL-10 protein concentration changes, preferably through Western Blot analysis.

• One of the key proinflammatory transcription factor that is activated is NF-κB; therefore, authors must investigate its expression of it.

• One of the key events that is affected is the breach of the tight junction. Therefore, colon permeability along with tight junction protein expression must be investigated before it can be acceptable as a model that mimics IBD with complex etiology.

**********

6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: No

**********

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

Attachment

Submitted filename: PLOS ONE Review.pdf

pone.0311310.s002.pdf^{(71KB, pdf)}

PLoS One. 2024 Nov 21;19(11):e0311310. doi: 10.1371/journal.pone.0311310.r002

Author response to Decision Letter 0

9 Jun 2024

Pradeep Dudeja

Academic Editor

PLOS ONE

Dear Dr. Dudeja

Subject: Development of a novel complex inflammatory bowel disease mouse model: reproducing human inflammatory bowel disease etiologies in mice [PONE-D-24-05316R1]

Thank you for inviting us to submit a revised draft of our manuscript entitled, " Development of a novel complex inflammatory bowel disease mouse model: reproducing various human inflammatory bowel disease etiologies in mice" to PLOS ONE. We also appreciate the time and effort you and each of the reviewers have dedicated to providing insightful feedback on ways to strengthen our paper. Thus, it is with great pleasure that we resubmit our article for further consideration. We have incorporated changes that reflect the detailed suggestions you have graciously provided. We also hope that our edits and the responses we provide below satisfactorily address all the issues and concerns you and the reviewers have noted. Also, we declare that the funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

To facilitate your review of our revisions, the following is a point-by-point response to the questions and comments delivered in your letter dated 05 June 2024.

Proposals from Academic Editor

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at

https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and

https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf

Answer: We revised our manuscript based on the PLOS ONE style template.

2. Thank you for stating the following financial disclosure:

If the funders had no role, please state: "The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript." If this statement is not correct you must amend it as needed.

Please include this amended Role of Funder statement in your cover letter; we will change the online submission form on your behalf.

Answer: We added “role of funder statement” in our cover letter.

Comments from Reviewer #1:

The goal of this paper is to develop complex models that mimic IBD in humans more closely than currently available models. This is a descriptive paper focusing on some observations and does not delve into possible mechanisms. The authors are requested to address the following comments and provide clarifications.

1. How many new models have been developed? Two? HFD and HCD? State this in the title.

Answer: Additional experiments requested by Reviewer 2 confirmed that the HFD group was not suitable for the new IBD model. For this reason, we revised the entire manuscript and presented only HCD as a new model. The title has also been modified.

Answer: Thank you for your assessment. As the reviewer pointed out, the pre-revision manuscript concluded with a logical leap, without explaining the limitations of the previous IBD model and how those limitations were overcome. Based on these assessment, we revised the manuscript to determine how our results mimic human IBD, what the limitations of previous IBD models were, and how to overcome these limitations. The current IBD models are mainly chemically induced models or models using genetically modified animals. The biggest limitation of these models is that they are difficult to induce chronic features in human IBD and, unlike genetically modified models, have complex pathogenesis in humans. The advantage of our model is that it not only causes chronic inflammation but also overcomes the limitations of each IBD model by mixing various IBD factors rather than focusing on each IBD factor.

3. Line 153-154: What happens if WT animals are fed a HFD? Do they develop any signs of inflammation as the Il2rg deficient mice?

Answer: Based on our previous pilot study results, WT did not show signs of inflammation following high-fat diet feeding.

4. Line 264: Unclear what is meant by 6 types – the six observations?

Answer: Thank you for your suggestion. As the reviewer asked, “6 observation” is more appropriate than “6 types”, so we revised the corresponding word.

5. Line 310-312: Are there no other models that show these characteristics of inflammation? What makes the present model unique?

Answer: Characteristics of inflammation, such as ulcer and transmural inflammation seen in our model are also present in the TNBS-induced IBD model. However, TNBS induced colitis does not recapitulate the disease in terms of etiopathogenesis. For this reason our model have a unique advantage.

6. Line 315; When the authors state “gradually increased …” did they perform a time course to measure the increase in cytokine expression?

Answer: We meant “gradually increased” as inflammation worsened by the IBD factors added one by one. However, because there may be misunderstanding in interpretation, “gradually” was deleted from the sentence. Additionally, the same expressions were also deleted from the manuscript.but this was corrected because there may have been misunderstandings in the interpretation.

7. Line 317-318: If interferon gamma did not increase as anticipated, how do the authors reconcile this as being a good model for IBD.

Answer: Thank you for providing these insights. We performed ELISA on serum levels of cytokines and confirmed that interferon gamma showed a significant difference in the HCD group, unlike mRNA level. These conflicting results between mRNA and protein are consistent with previous studies suggesting that due to a synthesis delay between mRNA and protein. These result available in revised Fig 5. additional results in (p. 13, line 254-255), and discussion in (p. 19, line 391-394 with additional reference [46]) (Added and revised sentences marked with red color).

8. Line 324-325: How do the authors reconcile the increase in IL-10 in the HFD group with the latter being a model for IBD (MC). IF this is information in Ref 51, it should be explained better.

Answer: Additional experiments requested by Reviewer 2 confirmed that the HFD group was not suitable for the new IBD model. We concluded that IL-10 upregulation in the HFD group indicates the resolution of self-limiting inflammation, not becoming chronic form. This information is written in (p .19 line 395-400).

9. Line 331-332: Do the authors conclude that HCD mimics CD and HFD mimics MC based strictly on PCR results of cytokine expression?

Answer: Additional experiments requested by Reviewer 2 confirmed that the HFD group was not suitable for the new IBD model. However, unlike HFD, combining protein level and mRNA level results of cytokine confirms HCD mimics CD.

Answer: Thank you for your insight. To reflect the difficulty in understanding the plots, the figure and results were changed to F/B ratio to confirm the relative abundance of Firmicutese and Bacteriodetes more objectively. (p. 16 line 316-320, marked with red color)

Answer: We acknowledge that there was a lack of explanation for the sentence. The previous study shows that Erysipelotrichaceae is low in UC patients and high in obese conditions compared to Healthy control. The manuscript has been revised to include the relevant content. (p. 21 line 436-439, marked with red color)

12. Line 375: A stronger argument with more convincing comparisons to other models and data are needed to support this conclusion.

Answer: Opinions of the relative abundance of Rumincoccaceae, Lactobacillaceae, Akkermansiaceae, and Enterococcaceae between healthy control and IBD patients are controversial. However, when compared with previous research results on the microbiota of human IBD patients, this turned out to be different from our expectations. These changes in outcome are thought to be due to deletion of IL2rg, also known as the common gamma chain. The previous study that genetic background has a stronger impact on the composition of the microbiota than maternal inoculation or exogenous microbiota, which corresponded to our results. We revised the sentence and add a reference. (p. 21, line 448-449, additional reference [69], marked with red color.)

13. Line 381-382, the authors state the HCD model is good for the study of human CD and UC and yet the discussion on the data does not provide evidence on the connection to UC.

Answer: Thank you for your assessment. Based on the additional experimental results, the manuscript was revised as a whole, and the significant differences in TNF-α and NF-κB were indicated as evidence of the connection to UC.

14. Figures: The practice of embedding the figure legends in the text is not common and therefore a bit difficult to follow. The maximal details should be provided in the methods and those in the legend and figure should reflect the highlights. For example, the methods do not state how DSS was administered, but it is only stated in the figure 1.

Answer: Thank you for your suggestion. As your advice we checked the missing parts in the method and added the necessary information. The information about the administration of DSS for Fig 1, provided as an example is written in (p. 4 line 72-73, marked with red color)

15. All figure legends should state the “n” values even if they are the same for each experiment.

Answer: As your advice, we indicated “n” values in all figures.

16. Figure 1: The methods should clearly reflect what was done. Lines 62-90 were confusing to this reviewer. It could be interpreted as 56+17 = 73 days (which seems to be the case based on the figure) or as 56days on ND +56days on diet +17 days = 129 days. As written in this and previous page it could be either. Is “0” day, the day of birth or are they 8 weeks old at that stage. If the former, when were the animals weaned from their dams?

Answer: We agree that our expression was ambiguous. Our experimental design was 56+17=73 days. So we revised sentences that might cause confusion (p. 4 line 67-70, marked with red color). Additionally, day "0" is the start date of the experiment, when the mouse is 8 weeks old.전자인

17. Line 153-154 states that figure 1 shows “genetic factors were imitated….” This reviewer could not find that information in the figure. Please explain.

Answer: Thank you for pointing out the error. The relevant information appears in the previous study, so we revised the sentence and added a reference. (p. 10 line 184-185, marked with red color)

18. Figure 4: As done for figure 2 and 3, please indicate the cytokine being measured in the y-axes; it is difficult to follow if one has to refer back to the text.

Answer: As your advice, we indicated name of the target cytokine on the Y axis.

19. Figure 6: Please label Y-axes in panels B and C, as stated for Figure 4.

Answer: As your advice, we indicated label of the target cytokine on the Y axis. Fig 6. was changed to Fig 8. Because of the addition of other figures.

Comments from Editor:

The paper should be carefully reviewed for editorial and grammatical inconsistencies. A few examples are provided and this list is not complete

1. line 43, should read “… Clostridium difficile infections…”;

Answer: We revised sentence (p. 3, line 45) and marked it with red color.

2. line 65, the expansion of HCD should be provided when it is first used here;

Answer: In addition to the HCD you advised, we also revised full name of WT, ND, and HFD. The revised sentences marked with red color (p. 4 line 62-65, p. 5 84-88)

3. Line 94-97: the sentence is repeated;

Answer: We checked the repeated sentences and deleted them.

4. line 103: What is meant by “….performed independently on three individuals” – samples from three animals were analyzed or does it mean that the histopathological scoring and analyses (double blind) were conducted by three separate researchers?

Answer: Thank you for your suggestion. We describe this sentence to mean that scoring and analyses were conducted by three separate researchers. We recognized that sentence is ambiguous, so we modified it and marked with red color. (p. 6, line 104)

5. Line 303: Do the authors mean altered bacterial environment (including composition) when they state “bacteria”?

Answer: We agree that our expression was ambiguous. As the editor pointed out, "bacteria" means a change in the bacterial environment, also known as dysbiosis. Due to the extensive revision of the Discussion, the relevant content disappeared, but the ambiguous expression in the manuscript was corrected to dysbiosis.

Comments from Reviewer #2:

In this study, the authors have developed the mouse model of IBD using various human IBD etiologies. However, many major concerns need to be addressed.

1. A change in the myeloperoxidase enzyme activity must support the change in the colon length.

Answer: Thank you for your suggestion. As a result of MPO activity assay, it was confirmed that MPO activity increased as the colon length decreased. Those results are available in revised Fig 3. additional results in (p. 11, line 209-214), and discussion in (p. 19, line 383-385) (Added and revised sentences marked with red color).

2. A complete picture of the Swiss roll must be provided along with the magnified inserts. The scale bar must be included in the picture.

Answer: We added entire picture of swiss roll in Fig 3. Also, the scale bar added in both low and high magnification pictures.

3. What does the bar diagram Fig 2B indicating the histopathological scoring indicate?

Answer: The bar diagram of histopathological scoring is the score calculated based on Table 1. in the manuscript.

4. The Fig2C bar diagram showing HFD and HCD standard deviation (SD) is very high. With this high SD, having a statistical significance in what is depicted is unrealistic. Therefore, statistics analysis must be revisited.

Answer: Thank you for providing this insight. The review made us realize that our statistics were inadequate. Because the number of samples per group was not large enough, the statistical analyses were changed to the Kruskal-Wallis test, and SD was also changed to SEM.

5. To evaluate the reliability of the newly established IBD model, several parameters of key anti-inflammatory activity must be assessed. These include IL-6, IL-1B, TNF-alpha, and CX

Attachment

Submitted filename: Response to Reviewers.docx

pone.0311310.s003.docx^{(27.3KB, docx)}

PLoS One. doi: 10.1371/journal.pone.0311310.r003

Decision Letter 1

Pradeep Dudeja

6 Aug 2024

PONE-D-24-05316R1Development of a novel complex inflammatory bowel disease mouse model: reproducing human inflammatory bowel disease etiologies in micePLOS ONE

Dear Dr. Choi,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process. Both the reviewers felt that the manuscript has significantly improved and authors have addressed almost all of the concerns. However, one of the reviewer raised some minor concerns which related to issues concerning the comparisons of certain groups and clarification of some queries. We invite the authors to address these minor concerns and submit a re-revised version. Please submit your revised manuscript by Sep 20 2024 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.
An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

We look forward to receiving your revised manuscript.

Kind regards,

Pradeep Dudeja

Academic Editor

PLOS ONE

Journal Requirements:

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

Reviewer #3: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #1: Yes

Reviewer #3: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #3: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

Reviewer #1: Yes

Reviewer #3: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #1: Yes

Reviewer #3: Yes

**********

6. Review Comments to the Author

Reviewer #1: The authors have done a good job in revising the manuscript and responding to this reviewer’s concerns. Thank you. There are a few questions –

Page 14, Line 265-66: Can you comment on whether the HFD group was statistically different from WT or ND in mRNA or protein for IL-10?

Page 16-17: Line 332-334: The two sentences appear contradictory – does Enterococcaceae increase in the WT group as suggested by the 2nd sentence?

Page 19 line 396-397: As written here it is unclear whether the change in IL-10 in HFD is associated with worsening or resolving the disease. In responses to the previous review (#8), the authors provide a clearer explanation and I recommend that language should be included here instead. “We concluded that IL-10 upregulation in the HFD group indicates the resolution of self-limiting inflammation, not becoming chronic form. This information is written in (p .19 line 395-400).”

Page 32, Line 410: “This result indicates…..” is an incomplete sentence and should be deleted.

Reviewer #3: The authors have addressed most of the concerns raised by the reviewers. However, the authors should consider the following suggestions:

1. Previous studies have shown an increase in the abundance of Proteobacteria (phylum associated with wide variety of pathogens) in CD patients (Ref#62). Figure 8A shows an increase in the abundance of Proteobacteria in HCD group compared to WT, ND and HFD groups. However, the authors failed to elaborate on this aspect in the revised manuscript. Moreover, further explanation on this aspect would be more convincing to establish that HCD model is good for the study of human CD.

2. Any specific reason as to why HCD gp was not compared to WT and ND groups in Figs. 4D and 5D?

3. Please be consistent. Also compare HCD gp with ND gp in Figs. 4B, 4E, 4F, 6C and 6D.

4. Did the authors examine NF�B (p65) protein levels in nuclear fraction of colon lysates? If yes, NF�B (p65) levels should be normalized to a nuclear protein, Lamin B1

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #3: No

**********

PLoS One. 2024 Nov 21;19(11):e0311310. doi: 10.1371/journal.pone.0311310.r004

Author response to Decision Letter 1

12 Aug 2024

Dear Dr. Dudeja

Subject: Development of a novel complex inflammatory bowel disease mouse model: reproducing human inflammatory bowel disease etiologies in mice [PONE-D-24-05316R1]

Thank you for inviting us to submit a revised draft of our manuscript entitled, "Development of a novel complex inflammatory bowel disease mouse model: reproducing human inflammatory bowel disease etiologies in mice" to PLOS ONE. We appreciate the time and effort you and the reviewers have dedicated to providing insightful feedback to strengthen our paper. We are pleased to resubmit our article for further consideration, having incorporated the detailed suggestions provided. We believe that our edits and the responses below adequately address all the issues and concerns raised by you and the reviewers.

To facilitate your review of our revisions, the following is a point-by-point response to the questions and comments delivered in your letter dated 12 August 2024.

Comments from Reviewer #1:

The authors have done a good job in revising the manuscript and responding to this reviewer’s concerns. Thank you. There are a few questions

1. Page 14, Line 265-66: Can you comment on whether the HFD group was statistically different from WT or ND in mRNA or protein for IL-10?

A: Thank you for providing these insights. Although the WT and ND groups show lower Il-10 levels in both mRNA and protein analyses, no significant differences were observed compared to the HFD group. These results may be attributed to the use of nonparametric tests due to the limited sample size. We have included these additional results (p.13 line 257-260, p.14 line 279-282) and discussion (p.21 line 437-440) in our revised manuscript.

2. Page 16-17: Line 332-334: The two sentences appear contradictory – does Enterococcaceae increase in the WT group as suggested by the 2nd sentence?

A: We agree that our expression was ambiguous. We intended to explain that the relative abundance of Enterococcaceae increased in the ND, HFD, and HCD groups as factors known to influence IBD were applied, whereas the WT group deviated from this trend. The relative abundance of Enterococcaceae in the WT group was higher than in the ND and HFD groups. We have included this additional explanation in our revised manuscript (P.17-18 line 358-361). Additionally, we also revised the sentences concerning Ruminococcaceae and Lactobacillaceae to avoid potential confusion. (P.17 line 356-358)

3. Page 19 line 396-397: As written here it is unclear whether the change in IL-10 in HFD is associated with worsening or resolving the disease. In responses to the previous review (#8), the authors provide a clearer explanation and I recommend that language should be included here instead. “We concluded that IL-10 upregulation in the HFD group indicates the resolution of self-limiting inflammation, not becoming chronic form. This information is written in (p.19 line 395-400).”

A: Thank you for your suggestion. We agree that our expression was confusing, so we revised our manuscript to be more obvious (p. 20 line 423-425).

4. Page 32, Line 410: “This result indicates…..” is an incomplete sentence and should be deleted.

A: Thank you for your advice. As your advice, we deleted the incomplete sentence.

Comments from Reviewer #3:

The authors have addressed most of the concerns raised by the reviewers. However, the authors should consider the following suggestions:

A: Thank you for providing these insights. In addition to the increased abundance of Proteobacteria in the HCD group, we also discussed the reduced abundance of Actinobacteriota, which is known to be decreased in CD and UC patients. These results are presented in our revised result (p.17 line 335-341) and discussion (p.21 line 453-457) sections, along with the newly added Fig. 8B.

2. Any specific reason as to why HCD gp was not compared to WT and ND groups in Figs. 4D and 5D?

A: Thank you for your insightful feedback. Although the HCD group showed lower levels of Il-10 in both mRNA and protein analyses, no statistically significant differences were observed compared to the WT and ND groups, so we initially did not include this data. However, following the recommendations of Reviewer 1 and Reviewer 3, we have now added these results to the revised manuscript (p.13 line 257-260, p.14 line 279-282). As mentioned in our response to Reviewer 1's Question 1, the lack of statistical significance may be attributed to the use of non-parametric tests due to the limited sample size.

3. Please be consistent. Also compare HCD gp with ND gp in Figs. 4B, 4E, 4F, 6C and 6D.

A: As in our response to Question 2, no statistically significant differences were observed in Fig. 4B, 4E, 4F, 6C, and 6D, so we initially did not mention these results. However, following the reviewers' recommendations, we have now included a comparison of expression levels and significance between the HCD group and the ND, WT, and HFD groups in Fig. 4, Fig. 5, and Fig. 6 in the revised manuscript. (p. 13 line 243-255, p. 14 line 264-278, p. 15 line 301-306)

4. Did the authors examine NF�B (p65) protein levels in nuclear fraction of colon lysates? If yes, NF�B (p65) levels should be normalized to a nuclear protein, Lamin B1

A: We normalized p65 activation to β-actin because we aimed to assess the overall phosphorylation status of p65 by examining its protein levels in total lysates without distinguishing between the cytoplasm and nucleus. However, while preparing our response to the revision, we realized that our manuscript did not sufficiently mention the phosphorylation of NF-κB, and we had incorrectly described the antibody used. We have now corrected these details in our revised manuscript. (p. 9 line 148, p. 15 line 300, Fig. 6A, Fig 6C and supplemental figure)

Again, thank you for giving us the opportunity to strengthen our manuscript with your valuable comments and queries. We have worked hard to incorporate your feedback and hope that these revisions persuade you to accept our submission.

Attachment

Submitted filename: Response to Reviewers.docx

pone.0311310.s004.docx^{(19.9KB, docx)}

PLoS One. doi: 10.1371/journal.pone.0311310.r005

Decision Letter 2

Pradeep Dudeja

2 Sep 2024

Development of a novel complex inflammatory bowel disease mouse model: reproducing human inflammatory bowel disease etiologies in mice

PONE-D-24-05316R2

Dear Dr. Choi,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

An invoice will be generated when your article is formally accepted. Please note, if your institution has a publishing partnership with PLOS and your article meets the relevant criteria, all or part of your publication costs will be covered. Please make sure your user information is up-to-date by logging into Editorial Manager at Editorial Manager® and clicking the ‘Update My Information' link at the top of the page. If you have any questions relating to publication charges, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Pradeep Dudeja

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

PLoS One. doi: 10.1371/journal.pone.0311310.r006

Acceptance letter

Pradeep Dudeja

19 Sep 2024

PONE-D-24-05316R2

PLOS ONE

Dear Dr. Choi,

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now being handed over to our production team.

At this stage, our production department will prepare your paper for publication. This includes ensuring the following:

* All references, tables, and figures are properly cited

* All relevant supporting information is included in the manuscript submission,

* There are no issues that prevent the paper from being properly typeset

If revisions are needed, the production department will contact you directly to resolve them. If no revisions are needed, you will receive an email when the publication date has been set. At this time, we do not offer pre-publication proofs to authors during production of the accepted work. Please keep in mind that we are working through a large volume of accepted articles, so please give us a few weeks to review your paper and let you know the next and final steps.

Lastly, if your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

If we can help with anything else, please email us at customercare@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Pradeep Dudeja

Academic Editor

PLOS ONE

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

S1 Raw image. Uncropped images of blot presented in Fig 6A & 6B.

(PDF)

pone.0311310.s001.pdf^{(521.6KB, pdf)}

Attachment

Submitted filename: PLOS ONE Review.pdf

pone.0311310.s002.pdf^{(71KB, pdf)}

Attachment

Submitted filename: Response to Reviewers.docx

pone.0311310.s003.docx^{(27.3KB, docx)}

Attachment

Submitted filename: Response to Reviewers.docx

pone.0311310.s004.docx^{(19.9KB, docx)}

Data Availability Statement

All relevant data are within the manuscript.

[pone.0311310.ref001] 1.Lewis JD, Abreu MT. Diet as a Trigger or Therapy for Inflammatory Bowel Diseases. Gastroenterology. 2017. Feb;152(2):398–414.e6. doi: 10.1053/j.gastro.2016.10.019 [DOI] [PubMed] [Google Scholar]

[pone.0311310.ref002] 2.Cheng L, Jin H, Qiang Y, Wu S, Yan C, Han M, et al. High fat diet exacerbates dextran sulfate sodium induced colitis through disturbing mucosal dendritic cell homeostasis. Int Immunopharmacol. 2016. Nov;40:1–10. doi: 10.1016/j.intimp.2016.08.018 [DOI] [PubMed] [Google Scholar]

[pone.0311310.ref003] 3.Sugihara K, Kamada N. Diet-Microbiota Interactions in Inflammatory Bowel Disease. Nutrients. 2021. May 1;13(5):1533. doi: 10.3390/nu13051533 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0311310.ref004] 4.Ananthakrishnan AN, Bernstein CN, Iliopoulos D, Macpherson A, Neurath MF, Ali RAR, et al. Environmental triggers in IBD: a review of progress and evidence. Nat Rev Gastroenterol Hepatol. 2018. Jan;15(1):39–49. doi: 10.1038/nrgastro.2017.136 [DOI] [PubMed] [Google Scholar]

[pone.0311310.ref005] 5.Mentella MC, Scaldaferri F, Pizzoferrato M, Gasbarrini A, Miggiano GAD. Nutrition, IBD and Gut Microbiota: A Review. Nutrients. 2020. Mar 29;12(4):944. doi: 10.3390/nu12040944 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0311310.ref006] 6.Sanmarco LM, Chao CC, Wang YC, Kenison JE, Li Z, Rone JM, et al. Identification of environmental factors that promote intestinal inflammation. Nature. 2022. Nov;611(7937):801–809. doi: 10.1038/s41586-022-05308-6 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0311310.ref007] 7.Kim JJ, Shajib MS, Manocha MM, Khan WI. Investigating intestinal inflammation in DSS-induced model of IBD. J Vis Exp. 2012. Feb 1;(60):3678. doi: 10.3791/3678 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0311310.ref008] 8.Ng SC, Shi HY, Hamidi N, Underwood FE, Tang W, Benchimol EI, et al. Worldwide incidence and prevalence of inflammatory bowel disease in the 21st century: a systematic review of population-based studies. Lancet. 2017. Dec 23;390(10114):2769–2778. doi: 10.1016/S0140-6736(17)32448-0 [DOI] [PubMed] [Google Scholar]

[pone.0311310.ref009] 9.Lamb CA, Kennedy NA, Raine T, Hendy PA, Smith PJ, Limdi JK, et al. British Society of Gastroenterology consensus guidelines on the management of inflammatory bowel disease in adults. Gut. 2019. Dec;68(Suppl 3):s1–s106. doi: 10.1136/gutjnl-2019-318484 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0311310.ref010] 10.van Nood E, Vrieze A, Nieuwdorp M, Fuentes S, Zoetendal EG, de Vos WM, et al. Duodenal infusion of donor feces for recurrent Clostridium difficile. N Engl J Med. 2013. Jan 31;368(5):407–15. [DOI] [PubMed] [Google Scholar]

[pone.0311310.ref011] 11.Caldeira LF, Borba HH, Tonin FS, Wiens A, Fernandez-Llimos F, Pontarolo R, et al. Fecal microbiota transplantation in inflammatory bowel disease patients: A systematic review and meta-analysis. PLoS One. 2020. Sep 18;15(9):e0238910. doi: 10.1371/journal.pone.0238910 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0311310.ref012] 12.Shon WJ, Jung MH, Kim Y, Kang GH, Choi EY, Shin DM, et al. Sugar-sweetened beverages exacerbate high-fat diet-induced inflammatory bowel disease by altering the gut microbiome. J Nutr Biochem. 2023. Mar;113:109254. doi: 10.1016/j.jnutbio.2022.109254 [DOI] [PubMed] [Google Scholar]

[pone.0311310.ref013] 13.Shon WJ, Song JW, Oh SH, Lee KH, Seong H, You HJ, et al. Gut taste receptor type 1 member 3 is an intrinsic regulator of Western diet-induced intestinal inflammation. BMC Med. 2023. Apr 28;21(1):165. doi: 10.1186/s12916-023-02848-0 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0311310.ref014] 14.Park JI, Seo SM, Park JH, Jeon HY, Kim JY, Ryu SH, et al. A murine colitis model developed using a combination of dextran sulfate sodium and Citrobacter rodentium. J Microbiol. 2018. Apr;56(4):272–279. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0311310.ref015] 15.Grassl GA, Valdez Y, Bergstrom KS, Vallance BA, Finlay BB. Chronic enteric salmonella infection in mice leads to severe and persistent intestinal fibrosis. Gastroenterology. 2008. Mar;134(3):768–80. doi: 10.1053/j.gastro.2007.12.043 [DOI] [PubMed] [Google Scholar]

[pone.0311310.ref016] 16.Higgins LM, Frankel G, Douce G, Dougan G, MacDonald TT. Citrobacter rodentium infection in mice elicits a mucosal Th1 cytokine response and lesions similar to those in murine inflammatory bowel disease. Infect Immun. 1999. Jun;67(6):3031–9. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0311310.ref017] 17.Dieleman LA, Ridwan BU, Tennyson GS, Beagley KW, Bucy RP, Elson CO, et al. Dextran sulfate sodium-induced colitis occurs in severe combined immunodeficient mice. Gastroenterology. 1994. Dec;107(6):1643–52. doi: 10.1016/0016-5085(94)90803-6 [DOI] [PubMed] [Google Scholar]

[pone.0311310.ref018] 18.Arita M, Yoshida M, Hong S, Tjonahen E, Glickman JN, Petasis NA, et al. Resolvin E1, an endogenous lipid mediator derived from omega-3 eicosapentaenoic acid, protects against 2,4,6-trinitrobenzene sulfonic acid-induced colitis. Proc Natl Acad Sci U S A. 2005. May 24;102(21):7671–6. doi: 10.1073/pnas.0409271102 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0311310.ref019] 19.Boirivant M, Fuss IJ, Chu A, Strober W. Oxazolone colitis: A murine model of T helper cell type 2 colitis treatable with antibodies to interleukin 4. J Exp Med. 1998. Nov 16;188(10):1929–39. doi: 10.1084/jem.188.10.1929 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0311310.ref020] 20.Mombaerts P, Mizoguchi E, Grusby MJ, Glimcher LH, Bhan AK, Tonegawa S, et al. Spontaneous development of inflammatory bowel disease in T cell receptor mutant mice. Cell. 1993. Oct 22;75(2):274–82. doi: 10.1016/0092-8674(93)80069-q [DOI] [PubMed] [Google Scholar]

[pone.0311310.ref021] 21.Kühn R, Löhler J, Rennick D, Rajewsky K, Müller W. Interleukin-10-deficient mice develop chronic enterocolitis. Cell. 1993. Oct 22;75(2):263–74. doi: 10.1016/0092-8674(93)80068-p [DOI] [PubMed] [Google Scholar]

[pone.0311310.ref022] 22.Lee JH, Park JH, Nam TW, Seo SM, Kim JY, Lee HK, et al. Differences between immunodeficient mice generated by classical gene targeting and CRISPR/Cas9-mediated gene knockout. Transgenic Res. 2018. Jun;27(3):241–251. doi: 10.1007/s11248-018-0069-y [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0311310.ref023] 23.Laroui H, Ingersoll SA, Liu HC, Baker MT, Ayyadurai S, Charania MA, et al. Dextran sodium sulfate (DSS) induces colitis in mice by forming nano-lipocomplexes with medium-chain-length fatty acids in the colon. PLoS One. 2012;7(3):e32084. doi: 10.1371/journal.pone.0032084 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0311310.ref024] 24.Callahan BJ, McMurdie PJ, Rosen MJ, Han AW, Johnson AJ, Holmes SP, et al. DADA2: High-resolution sample inference from Illumina amplicon data. Nat Methods. 2016. Jul;13(7):581–3. doi: 10.1038/nmeth.3869 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0311310.ref025] 25.Segata N, Izard J, Waldron L, Gevers D, Miropolsky L, Garrett WS, et al. Metagenomic biomarker discovery and explanation. Genome Biol. 2011. Jun 24;12(6):R60. doi: 10.1186/gb-2011-12-6-r60 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0311310.ref026] 26.McDonald D, Jiang Y, Balaban M, Cantrell K, Zhu Q, Gonzalez A, et al. Greengenes2 enables a shared data universe for microbiome studies. BioRxiv [Preprint]. 2023. bioRxiv 520774. https://www.biorxiv.org/content/10.1101/2022.12.19.520774v2. [Google Scholar]

[pone.0311310.ref027] 27.Bolyen E, Rideout JR, Dillon MR, Bokulich NA, Abnet CC, Al-Ghalith GA, et al. Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nat Biotechnol. 2019. Aug;37(8):852–857. doi: 10.1038/s41587-019-0209-9 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0311310.ref028] 28.Bokulich NA, Kaehler BD, Rideout JR, Dillon M, Bolyen E, Knight R, et al. Optimizing taxonomic classification of marker-gene amplicon sequences with QIIME 2’s q2-feature-classifier plugin. Microbiome. 2018. May 17;6(1):90. doi: 10.1186/s40168-018-0470-z [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0311310.ref029] 29.Park, J. Y. et al. Do Different Samples From Pregnant Women and Their Neonates Share the Common Microbiome: A Prospective Cohort Study. Research Square [Preprint]. 2021 Research Square. https://www.researchsquare.com/article/rs-1062191/v1.

[pone.0311310.ref030] 30.Johansson ME, Phillipson M, Petersson J, Velcich A, Holm L, Hansson GC, et al. The inner of the two Muc2 mucin-dependent mucus layers in colon is devoid of bacteria. Proc Natl Acad Sci U S A. 2008. Sep 30;105(39):15064–9. doi: 10.1073/pnas.0803124105 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0311310.ref031] 31.Sokol H, Seksik P, Furet JP, Firmesse O, Nion-Larmurier I, Beaugerie L, et al. Low counts of Faecalibacterium prausnitzii in colitis microbiota. Inflamm Bowel Dis. 2009. Aug;15(8):1183–9. [DOI] [PubMed] [Google Scholar]

[pone.0311310.ref032] 32.Stojanov S, Berlec A, Štrukelj B. The Influence of Probiotics on the Firmicutes/Bacteroidetes Ratio in the Treatment of Obesity and Inflammatory Bowel disease. Microorganisms. 2020. Nov 1;8(11):1715. doi: 10.3390/microorganisms8111715 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0311310.ref033] 33.Allchin WH. A Discussion on "Ulcerative Colitis.": Introductory Address. Proc R Soc Med. 1909;2(Med Sect):59–75. [PMC free article] [PubMed] [Google Scholar]

[pone.0311310.ref034] 34.Crohn BB, Ginzburg L, Oppenheimer GD. Regional ileitis: a pathologic and clinical entity. JAMA. 1932;99(16):1323–1329. [Google Scholar]

[pone.0311310.ref035] 35.Kucharzik T, Ellul P, Greuter T, Rahier JF, Verstockt B, Abreu C, et al. ECCO Guidelines on the Prevention, Diagnosis, and Management of Infections in Inflammatory Bowel Disease. J Crohns Colitis. 2021. Jun 22;15(6):879–913. doi: 10.1093/ecco-jcc/jjab052 [DOI] [PubMed] [Google Scholar]

[pone.0311310.ref036] 36.Baydi Z, Limami Y, Khalki L, Zaid N, Naya A, Mtairag EM, et al. An Update of Research Animal Models of Inflammatory Bowel Disease. ScientificWorldJournal. 2021. Dec 13;2021:7479540. doi: 10.1155/2021/7479540 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0311310.ref037] 37.Katsandegwaza B, Horsnell W, Smith K. Inflammatory Bowel Disease: A Review of Pre-Clinical Murine Models of Human Disease. Int J Mol Sci. 2022. Aug 19;23(16):9344. doi: 10.3390/ijms23169344 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0311310.ref038] 38.Lee CH, Koh SJ, Radi ZA, Habtezion A. Animal models of inflammatory bowel disease: novel experiments for revealing pathogenesis of colitis, fibrosis, and colitis-associated colon cancer. Intest Res. 2023. Jul;21(3):295–305. doi: 10.5217/ir.2023.00029 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0311310.ref039] 39.Mills SC, von Roon AC, Tekkis PP, Orchard TR. Crohn’s disease. BMJ Clin Evid. 2011. Apr 27;2011:0416. [PMC free article] [PubMed] [Google Scholar]

[pone.0311310.ref040] 40.Saiki T Myeloperoxidase concentrations in the stool as a new parameter of inflammatory bowel disease. Kurume Med J. 1998. 45;69–73. doi: 10.2739/kurumemedj.45.69 [DOI] [PubMed] [Google Scholar]

[pone.0311310.ref041] 41.Günther C, Martini E, Wittkopf N, Amann K, Weigmann B, Neumann H, et al. Caspase-8 regulates TNF-α-induced epithelial necroptosis and terminal ileitis. Nature. 2011. Sep 14;477(7364):335–9. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0311310.ref042] 42.McAlindon ME, Hawkey CJ, Mahida YR. Expression of interleukin 1 beta and interleukin 1 beta converting enzyme by intestinal macrophages in health and inflammatory bowel disease. Gut. 1998. Feb;42(2):214–9. doi: 10.1136/gut.42.2.214 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0311310.ref043] 43.Ostvik AE, Granlund AV, Bugge M, Nilsen NJ, Torp SH, Waldum HL, et al. Enhanced expression of CXCL10 in inflammatory bowel disease: potential role of mucosal Toll-like receptor 3 stimulation. Inflamm Bowel Dis. 2013. Feb;19(2):265–74. doi: 10.1002/ibd.23034 [DOI] [PubMed] [Google Scholar]

[pone.0311310.ref044] 44.Langer V, Vivi E, Regensburger D, Winkler TH, Waldner MJ, Rath T, et al. IFN-γ drives inflammatory bowel disease pathogenesis through VE-cadherin-directed vascular barrier disruption. J Clin Invest. 2019. Nov;129(11):4691–4707. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0311310.ref045] 45.Liu Y, Beyer A, Aebersold R. On the Dependency of Cellular Protein Levels on mRNA Abundance. Cell. 2016. Apr;165(3):535–50. doi: 10.1016/j.cell.2016.03.014 [DOI] [PubMed] [Google Scholar]

[pone.0311310.ref046] 46.Asseman C, Mauze S, Leach MW, Coffman RL, Powrie F. An essential role for interleukin 10 in the function of regulatory T cells that inhibit intestinal inflammation. J Exp Med. 1999. Oct;190(7):995–1004. doi: 10.1084/jem.190.7.995 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0311310.ref047] 47.Lin JX, Leonard WJ. The Common Cytokine Receptor γ Chain Family of Cytokines. Cold Spring Harb Perspect Biol. 2018. Sep;10(9):a028449. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0311310.ref048] 48.Liu T, Zhang L, Joo D, Sun SC. NF-κB signaling in inflammation. Signal Transduct Target Ther. 2017;2:17023–. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0311310.ref049] 49.Luettig J, Rosenthal R, Barmeyer C, Schulzke JD. Claudin-2 as a mediator of leaky gut barrier during intestinal inflammation. Tissue Barriers. 2015. Apr;3(1–2):e977176. doi: 10.4161/21688370.2014.977176 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0311310.ref050] 50.Landy J, Ronde E, English N, Clark SK, Hart AL, Knight SC, et al. Tight junctions in inflammatory bowel diseases and inflammatory bowel disease associated colorectal cancer. World J Gastroenterol. 2016. Mar;22(11):3117–26. doi: 10.3748/wjg.v22.i11.3117 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0311310.ref051] 51.Xiao L, Sonne SB, Feng Q, Chen N, Xia Z, Li X, et al. High-fat feeding rather than obesity drives taxonomical and functional changes in the gut microbiota in mice. Microbiome. 2017. Apr 8;5(1):43. doi: 10.1186/s40168-017-0258-6 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0311310.ref052] 52.Zhang Q, Wu Y, Wang J, Wu G, Long W, Xue Z, et al. Accelerated dysbiosis of gut microbiota during aggravation of DSS-induced colitis by a butyrate-producing bacterium. Sci Rep. 2016. Jun 6;6:27572. doi: 10.1038/srep27572 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0311310.ref053] 53.Pascal V, Pozuelo M, Borruel N, Casellas F, Campos D, Santiago A, et al. A microbial signature for Crohn’s disease. Gut. 2017. May;66(5):813–822. doi: 10.1136/gutjnl-2016-313235 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0311310.ref054] 54.Halfvarson J, Brislawn CJ, Lamendella R, Vázquez-Baeza Y, Walters WA, Bramer LM, et al. Dynamics of the human gut microbiome in inflammatory bowel disease. Nat Microbiol. 2017. Feb 13;2:17004. doi: 10.1038/nmicrobiol.2017.4 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0311310.ref055] 55.Lewis JD, Chen EZ, Baldassano RN, Otley AR, Griffiths AM, Lee D, et al. Inflammation, Antibiotics, and Diet as Environmental Stressors of the Gut Microbiome in Pediatric Crohn’s Disease. Cell Host Microbe. 2015. Oct 14;18(4):489–500. doi: 10.1016/j.chom.2015.09.008 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0311310.ref056] 56.Imhann F, Vich Vila A, Bonder MJ, Fu J, Gevers D, Visschedijk MC, et al. Interplay of host genetics and gut microbiota underlying the onset and clinical presentation of inflammatory bowel disease. Gut. 2018. Jan;67(1):108–119. doi: 10.1136/gutjnl-2016-312135 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0311310.ref057] 57.Moustafa A, Li W, Anderson EL, Wong EHM, Dulai PS, Sandborn WJ, et al. Genetic risk, dysbiosis, and treatment stratification using host genome and gut microbiome in inflammatory bowel disease. Clin Transl Gastroenterol. 2018. Jan 18;9(1):e132. doi: 10.1038/ctg.2017.58 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0311310.ref058] 58.Franzosa EA, Sirota-Madi A, Avila-Pacheco J, Fornelos N, Haiser HJ, Reinker S, et al. Gut microbiome structure and metabolic activity in inflammatory bowel disease. Nat Microbiol. 2019. Feb;4(2):293–305. doi: 10.1038/s41564-018-0306-4 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0311310.ref059] 59.Papa E, Docktor M, Smillie C, Weber S, Preheim SP, Gevers D, et al. Non-invasive mapping of the gastrointestinal microbiota identifies children with inflammatory bowel disease. PLoS One. 2012;7(6):e39242. doi: 10.1371/journal.pone.0039242 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0311310.ref060] 60.Vich Vila A, Imhann F, Collij V, Jankipersadsing SA, Gurry T, Mujagic Z, et al. Gut microbiota composition and functional changes in inflammatory bowel disease and irritable bowel syndrome. Sci Transl Med. 2018. Dec 19;10(472):eaap8914. doi: 10.1126/scitranslmed.aap8914 [DOI] [PubMed] [Google Scholar]

[pone.0311310.ref061] 61.Alam MT, Amos GCA, Murphy ARJ, Murch S, Wellington EMH, Arasaradnam RP. Microbial imbalance in inflammatory bowel disease patients at different taxonomic levels. Gut Pathog. 2020. Jan;12:1. doi: 10.1186/s13099-019-0341-6 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0311310.ref062] 62.Kaakoush NO. Insights into the Role of Erysipelotrichaceae in the Human Host. Front Cell Infect Microbiol. 2015. Nov 20;5:84. doi: 10.3389/fcimb.2015.00084 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0311310.ref063] 63.Everard A, Belzer C, Geurts L, Ouwerkerk JP, Druart C, Bindels LB, et al. Cross-talk between Akkermansia muciniphila and intestinal epithelium controls diet-induced obesity. Proc Natl Acad Sci U S A. 2013. May 28;110(22):9066–71. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0311310.ref064] 64.Chang CS, Liao YC, Huang CT, Lin CM, Cheung CHY, Ruan JW, et al. Identification of a gut microbiota member that ameliorates DSS-induced colitis in intestinal barrier enhanced Dusp6-deficient mice. Cell Rep. 2021. Nov 23;37(8):110016. doi: 10.1016/j.celrep.2021.110016 [DOI] [PubMed] [Google Scholar]

[pone.0311310.ref065] 65.Lagkouvardos I, Lesker TR, Hitch TCA, Gálvez EJC, Smit N, Neuhaus K, et al. Sequence and cultivation study of Muribaculaceae reveals novel species, host preference, and functional potential of this yet undescribed family. Microbiome. 2019. Feb 19;7(1):28. doi: 10.1186/s40168-019-0637-2 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0311310.ref066] 66.Wang H, Zhou C, Huang J, Kuai X, Shao X. The potential therapeutic role of Lactobacillus reuteri for treatment of inflammatory bowel disease. Am J Transl Res. 2020. May 15;12(5):1569–1583. [PMC free article] [PubMed] [Google Scholar]

[pone.0311310.ref067] 67.Huynh U, Zastrow ML. Metallobiology of Lactobacillaceae in the gut microbiome. J Inorg Biochem. 2023. Jan;238:112023. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0311310.ref068] 68.Korach-Rechtman H, Freilich S, Gerassy-Vainberg S, Buhnik-Rosenblau K, Danin-Poleg Y, Bar H, et al. Murine Genetic Background Has a Stronger Impact on the Composition of the Gut Microbiota than Maternal Inoculation or Exposure to Unlike Exogenous Microbiota. Appl Environ Microbiol. 2019. Aug; 85(18):e00826–19. doi: 10.1128/AEM.00826-19 [DOI] [PMC free article] [PubMed] [Google Scholar]

PERMALINK

Development of a novel complex inflammatory bowel disease mouse model: Reproducing human inflammatory bowel disease etiologies in mice

Sun-Min Seo

Na-Won Kim

Eun-Seon Yoo

Ji-Hun Lee

Ah-Reum Kang

Han-Bi Jeong

Won-Yong Shim

Dong-Hyun Kim

Young-Jun Park

Kieun Bae

Kyong-Ah Yoon

Yang-Kyu Choi

Roles

Abstract

1. Introduction

2. Methods

2.1. Experimental design

Fig 1. Schematic diagram of the experimental design of a complex IBD mouse model.

2.2. Histopathology

Table 1. Histopathological scoring criteria for IBD.

2.3. Myeloperoxidase assay

2.4. Cytokine evaluation

Table 2. Specific primers for the target cytokines.

2.5. Enzyme-linked immunosorbent assay (ELISA)

2.6. Western blot

2.7. Extraction and sequencing of DNA

2.8. Biome analysis

2.9. Statistical analysis

3. Results

3.1. Gross lesion and histopathological differences induced by the combination of IBD-affecting factors

Fig 2. Colon length changes according to IBD-exacerbated factors in Il2rg-deficient mice.

Fig 3. Histopathological analysis, histopathological scoring, and MPO activity of the colons of each group.

3.2. Inflammatory and anti-inflammatory cytokine expression differed depending on the combination of IBD-affecting factors

Fig 4. The relative expression levels of the pro-inflammatory and anti-inflammatory cytokine.

Fig 5. The protein levels of the pro-inflammatory and anti-inflammatory cytokine.

3.3. Combination of IBD-affecting factors exacerbate inflammation and loosen the intestinal barrier

Fig 6. The expression of NF-κB p65 and Claudin-2.

3.4. Changes in the gut microbiota due to factors affecting IBD

Fig 7. Characteristics of the bacterial community between groups.

Fig 8. Relative abundance analysis between groups.

4. Discussion

Supporting information

Data Availability

Funding Statement

References

Decision Letter 0

Pradeep Dudeja

Roles

Author response to Decision Letter 0

Decision Letter 1

Pradeep Dudeja

Roles

Author response to Decision Letter 1

Decision Letter 2

Pradeep Dudeja

Roles

Acceptance letter

Pradeep Dudeja

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

Similar articles

Cited by other articles

Links to NCBI Databases