The Role of Gut Microbiota in Inflammatory Bowel Disease: Mechanisms and Novel Therapeutic Approaches

A special issue of Microorganisms (ISSN 2076-2607). This special issue belongs to the section "Gut Microbiota".

Deadline for manuscript submissions: 15 July 2024 | Viewed by 3438

Special Issue Editors


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Guest Editor
Departamento de Nutrição, Universidade Federal da Paraíba, Joao Pessoa, Brazil
Interests: nutritional neuroscience; obesity; microbiology; clinical nutrition

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Guest Editor
Instituto Tecnológico Superior de Tacámbaro, Tacámbaro, Mexico
Interests: obesity; diabetes; hypothalamic inflammation; functional foods; energy balance

Special Issue Information

Dear Colleagues,

Inflammatory bowel disease (IBD) is a chronic inflammatory disorder characterized by an abnormal immune response to the gut microbiota. Recent studies have demonstrated that dysbiosis plays a significant role in the pathogenesis of IBD. Dysbiosis in IBD is characterized by decreased diversity of gut microbiota, changes in gut microbiota composition, and increased abundance of pathogenic bacteria. The mechanisms by which dysbiosis contributes to IBD are complex and multifactorial. Understanding the role of gut microbiota in IBD has led to the development of novel therapeutic approaches targeting the gut microbiota. Probiotics, prebiotics, symbiotic, and psychobiotics have been used to improve gut microbiota composition and reduce intestinal inflammation in IBD. Furthermore, traditional medicine and complementary and alternative medicines (CAMs) continue to be studied to mitigate the pathophysiology of IBD. Faecal microbiota transplantation (FMT) has also been shown to be an effective treatment for IBD. Dysbiosis plays a crucial role in IBD pathogenesis, and understanding the mechanisms underlying dysbiosis can lead to the development of novel therapies targeting the gut microbiota. Animal studies and clinical trials are currently ongoing to evaluate the efficacy and safety of these novel therapeutic approaches for IBD.

Dr. Jailane De Souza Aquino
Dr. Omar Guzman-Quevedo
Guest Editors

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Keywords

  • Crohn’s disease
  • ulcerative colitis
  • diets
  • dysbiosis
  • faecal microbiota transplantation
  • immunomodulation
  • metagenomics
  • herbal medicines
  • probiotics
  • prebiotics

Published Papers (3 papers)

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14 pages, 2897 KiB  
Article
A Machine Learning-Based Diagnostic Model for Crohn’s Disease and Ulcerative Colitis Utilizing Fecal Microbiome Analysis
by Hyeonwoo Kim, Ji Eun Na, Sangsoo Kim, Tae-Oh Kim, Soo-Kyung Park, Chil-Woo Lee, Kyeong Ok Kim, Geom-Seog Seo, Min Suk Kim, Jae Myung Cha, Ja Seol Koo and Dong-Il Park
Microorganisms 2024, 12(1), 36; https://doi.org/10.3390/microorganisms12010036 - 24 Dec 2023
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Abstract
Recent research has demonstrated the potential of fecal microbiome analysis using machine learning (ML) in the diagnosis of inflammatory bowel disease (IBD), mainly Crohn’s disease (CD) and ulcerative colitis (UC). This study employed the sparse partial least squares discriminant analysis (sPLS-DA) ML technique [...] Read more.
Recent research has demonstrated the potential of fecal microbiome analysis using machine learning (ML) in the diagnosis of inflammatory bowel disease (IBD), mainly Crohn’s disease (CD) and ulcerative colitis (UC). This study employed the sparse partial least squares discriminant analysis (sPLS-DA) ML technique to develop a robust prediction model for distinguishing among CD, UC, and healthy controls (HCs) based on fecal microbiome data. Using data from multicenter cohorts, we conducted 16S rRNA gene sequencing of fecal samples from patients with CD (n = 671) and UC (n = 114) while forming an HC cohort of 1462 individuals from the Kangbuk Samsung Hospital Healthcare Screening Center. A streamlined pipeline based on HmmUFOTU was used. After a series of filtering steps, 1517 phylotypes and 1846 samples were retained for subsequent analysis. After 100 rounds of downsampling with age, sex, and sample size matching, and division into training and test sets, we constructed two binary prediction models to distinguish between IBD and HC and CD and UC using the training set. The binary prediction models exhibited high accuracy and area under the curve (for differentiating IBD from HC (mean accuracy, 0.950; AUC, 0.992) and CD from UC (mean accuracy, 0.945; AUC, 0.988)), respectively, in the test set. This study underscores the diagnostic potential of an ML model based on sPLS-DA, utilizing fecal microbiome analysis, highlighting its ability to differentiate between IBD and HC and distinguish CD from UC. Full article
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0 pages, 13136 KiB  
Article
Gut Bacterial Community Determines the Therapeutic Effect of Ginsenoside on Canine Inflammatory Bowel Disease by Modulating the Colonic Mucosal Barrier
by Aipeng Mao, Weigang Zhao, Yuhang Zhu, Fantao Kong, Danyang Chen, Huazhe Si and Chao Xu
Microorganisms 2023, 11(11), 2616; https://doi.org/10.3390/microorganisms11112616 - 24 Oct 2023
Cited by 1 | Viewed by 1196 | Correction
Abstract
Inflammatory bowel disease (IBD) comprises systemic inflammatory conditions primarily affecting the gastrointestinal tract, including Crohn’s disease and ulcerative colitis. This research aims to analyze the clinical symptoms and pathogenesis of a Dextran sodium sulfate (DSS)-induced canine IBD model and evaluate the restorative effect [...] Read more.
Inflammatory bowel disease (IBD) comprises systemic inflammatory conditions primarily affecting the gastrointestinal tract, including Crohn’s disease and ulcerative colitis. This research aims to analyze the clinical symptoms and pathogenesis of a Dextran sodium sulfate (DSS)-induced canine IBD model and evaluate the restorative effect of ginsenoside from a pathogenesis perspective. We established the DSS-induced canine IBD model and studied the pathological mechanisms. Additionally, we examined the therapeutic effect of ginsenosides by assessing the Canine Inflammatory Bowel Disease Activity Index (CIBDAI), C-reactive protein (CRP) levels, colonic tissue morphology, protein expression, and mucosal bacterial community analysis. Our findings revealed a total ginsenoside content of 22.7% in the ginsenoside extract. Animal experiments demonstrated that dogs with IBD exhibited decreased mental state, significantly increased CIBDAI and CRP levels, disrupted colonic epithelial tissue structure, decreased expression of mucin, tight junctions, and adherens junctions, as well as reduced diversity of the colonic mucosal bacterial community. Furthermore, correlation analysis highlighted a total of 38 bacterial strains correlated with physiological indices. Significantly, ginsenoside treatment could improve these symptoms and reverse the relative abundance of some bacterial communities. In conclusion, alterations in the properties of the colonic mucus layer or the reduction in MUC2, its core component, in dogs with IBD can lead to bacterial penetration of the mucus layer and subsequent contact with intestinal epithelial cells, resulting in inflammation. Remarkably, ginsenoside intervention showcased the capacity to positively influence the relative abundance of bacteria and impact the colonic mucus layer properties, thereby offering promising prospects for IBD management and recovery. Full article
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1 pages, 138 KiB  
Correction
Correction: Mao et al. Gut Bacterial Community Determines the Therapeutic Effect of Ginsenoside on Canine Inflammatory Bowel Disease by Modulating the Colonic Mucosal Barrier. Microorganisms 2023, 11, 2616
by Aipeng Mao, Weigang Zhao, Yuhang Zhu, Fantao Kong, Danyang Chen, Huazhe Si and Chao Xu
Microorganisms 2024, 12(1), 158; https://doi.org/10.3390/microorganisms12010158 - 12 Jan 2024
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Abstract
The authors wish to make the following corrections to this paper [...] Full article
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