Numerous studies have accelerated the knowledge expansion on the role of gut microbiota in inflammatory bowel disease (IBD). However, the precise mechanisms behind host-microbe cross-talk remain largely undefined, due to the complexity of the human intestinal ecosystem and multiple external factors. In this review, we introduce the interactome concept to systematically summarize how intestinal dysbiosis is involved in IBD pathogenesis in terms of microbial composition, functionality, genomic structure, transcriptional activity, and downstream proteins and metabolites. Meanwhile, this review also aims to present an updated overview of the relevant mechanisms, high-throughput multi-omics methodologies, different types of multi-omics cohort resources, and computational methods used to understand host-microbiota interactions in the context of IBD. Finally, we discuss the challenges pertaining to the integration of multi-omics data in order to reveal host-microbiota cross-talk and offer insights into relevant future research directions.

The disturbance of gut microbiota and its metabolites are considered to be the causes of ulcerative colitis (UC), which leads to immune abnormalities. Diet is the most important regulator of gut microbiota; therefore, it has a beneficial impact on UC. A novel food ingredient, l-theanine, alters the gut microbiota, thereby regulating gut immunity. However, whether l-theanine prevents UC by altering the gut microbiota, as well as the underlying mechanisms, remains unknown. Here, l-theanine was used to optimize the gut microbiota and its metabolites. Furthermore, to explore the mechanism by which l-theanine prevents UC, an l-theanine fecal microbiota solution was used to prevent dextran sulfate sodium-induced UC via fecal microbiota transplantation. Improvements in the colonic structure, colon histology scores, immune factors (IL-10), and inflammatory factors (IL-1β) demonstrated the preventive effect of l-theanine on UC. The 16S rDNA and metabolomic results showed that tryptophan-, short chain fatty acid-, and bile acid-related microbiota, such as Muribaculaceae, Lachnospiraceae, Alloprevotella, and Prevotellaceae were the dominant. Flow cytometry results showed that l-theanine decreased helper T (Th)1 and Th17 immune responses, and increased Th2 and T-regulatory immune responses via regulation of antigen-presenting cell responses, such as dendritic cells and macrophages. Therefore, l-theanine regulated the immune response of colon CD4 + T cells to dendritic cell and macrophage antigen presentation via tryptophan-, short chain fatty acid-, and bile acid-related microbiota, thereby preventing dextran sulfate sodium-induced UC.

Mitochondrial dysfunction is increasingly recognized as a shared feature of Alzheimer's disease (AD) and inflammatory bowel disease (IBD), linked through overlapping pathways of hypoxia and immune dysregulation. Our study integrated transcriptomic and genetic analyses to uncover mitochondria-related mechanisms underlying these diseases. By analyzing multiple AD and IBD datasets through differential expression gene (DEG) analyses, biological pathway enrichment, and co-expression module construction, we identified hypoxia-induced mitochondrial dysfunction as a central risk factor for both conditions. Key findings revealed several mitochondrial-related genes shared between AD and IBD, including BCL6, PFKFB3, NDUFS3, and COX5B, which serve as critical regulators bridging mitochondrial and immune pathways. Drug enrichment analyses using Drug Signatures Database (DsigDB) and the Connectivity Map (cMAP) identified promising therapeutic candidates, including decitabine, DMOG, and estradiol, targeting shared regulators such as BCL6, PFKFB3, MAFF, and TGFBI. These drugs demonstrated potential to modulate mitochondrial autophagy and oxidative phosphorylation (OXPHOS), pathways enriched in the constructed interaction network with BCL6 and PFKFB3 as central nodes. Mendelian randomization (MR) analysis further identified MAP1LC3A as significantly associated with increased risk for both AD and IBD, while NME1 emerged as strongly protective, suggesting their roles as therapeutic targets. Our findings underscore hypoxia-induced mitochondrial dysfunction as a unifying mechanism in AD and IBD, mediated by hypoxia-inducible factor-1α (HIF-1α). By identifying key mitochondria-associated genes and pathways, this study highlights innovative therapeutic targets and contributes to a deeper understanding of the gut-brain interplay in neurodegeneration and chronic inflammation. These insights pave the way for precision medicine strategies targeting mitochondrial dysfunction in AD and IBD.

Background and Aims: Crohn's disease (CD) is a chronic inflammatory bowel disease (IBD) with a globally increasing prevalence, partially driven by alterations in gut microbiota. Although biological therapy is the first-line treatment for CD, a significant proportion of patients experience a primary non-response or secondary loss of response over time. This study aimed to explore the differences in gut microbiota among CD patients with divergent long-term responses to biological therapy, focusing on a long disease course. Methods: Sixteen CD patients who applied the biological agents for a while were enrolled in this study and were followed for one year, during which fecal specimens were collected monthly. Metagenomic analysis was used to determine the microbiota profiles in fecal samples. The response to biological therapy was evaluated both endoscopically and clinically. Patients were categorized into three groups based on their response: R (long-term remission), mA (mild active), and R2A group (remission to active). The differences in the gut microbiota among the groups were analyzed. Results: Significant differences in fecal bacterial composition were observed between the groups. The R2A group exhibited a notable decline in gut microbial diversity compared to the other two groups (p < 0.05). Patients in the R group had higher abundances of Akkermansia muciniphila, Bifidobacterium adolescentis, and Megasphaera elsdenii. In contrast, Veillonella parvula, Veillonella atypica, and Klebsiella pneumoniae were higher in the R2A group. Conclusions: Gut microbial diversity and specific bacterial significantly differed among groups, reflecting distinct characteristics between responders and non-responders.

Inflammatory bowel disease (IBD), including Crohn's disease (CD) and ulcerative colitis, is characterised by chronic and relapsing inflammation of the gastrointestinal tract, leading to significant morbidity and reduced quality of life. The global rise in IBD incidence is driven by a complex interplay of genetic, environmental, dietary and microbiome-related factors. Despite advancements in treatment, such as biologics, response rates remain variable, highlighting the need for personalised approaches. Recent research suggests that specific microbiome signatures may serve as biomarkers for predicting therapeutic efficacy, offering a potential tool for optimising treatment strategies in CD. The aim of the Optimising IBD Patient Treatment with Integrated Microbiome Investigation for Specialised Therapeutics (OPTIMIST) study is to evaluate microbiome profiles across various sample types in a Canadian CD cohort starting or already on advanced therapy, with the goal of developing predictive models for personalised therapeutics.

This study is a two-phase, longitudinal, prospective observational pilot study conducted in British Columbia, Canada, involving both CD patients and non-IBD controls. Phase 1 focuses on baseline microbiome differences across participant cohorts through cross-sectional analysis. Phase 2 follows participants over 12 months to assess microbiome changes and their association with treatment response. Stool samples, intestinal biopsies from the left colon, right colon and ileum, as well as mucosal wash samples from the proximal part of the distal colon, will undergo metagenomics, metaproteomics and metabolomics analyses to explore compositional and functional differences. Data will be analysed using alpha and beta diversity metrics, differential abundance analyses and multivariate analyses to identify microbiome-based predictors of therapeutic response.

Ethical approval was received by the Research Ethics Board (REB) of University of British Columbia-Providence Healthcare (UBC-PHC) with a REB number H23-02927. All amendments to the protocol are reported and adapted based on the requirements of the REB. The results of this study will be submitted to peer-reviewed journals and will be communicated in editorials/articles by the IBD Centre of BC and BC Children's Hospital Research Institute.

NCT06453720.

2024-06-21, version 3.0.

Perturbations in the intestinal microbiome are strongly linked to the pathogenesis of inflammatory bowel disease (IBD). Bacteria, fungi and viruses all make up part of a complex multi-kingdom community colonizing the gastrointestinal tract, often referred to as the gut microbiome. They can exert various effects on the host that can contribute to an inflammatory state. Advances in screening, multiomics and experimental approaches have revealed insights into host-microbiota interactions in IBD and have identified numerous mechanisms through which the microbiota and its metabolites can exert a major influence on the gastrointestinal tract. Looking into the future, the microbiome and microbiota-associated processes will be likely to provide unparalleled opportunities for novel diagnostic, therapeutic and diet-inspired solutions for the management of IBD through harnessing rationally designed microbial communities, powerful bacterial and fungal metabolites, individually or in combination, to foster intestinal health. In this Review, we examine the current understanding of the cross-kingdom gut microbiome in IBD, focusing on bacterial and fungal components and metabolites. We examine therapeutic and diagnostic opportunities, the microbial metabolism, immunity, neuroimmunology and microbiome-inspired interventions to link mechanisms of disease and identify novel research and therapeutic opportunities for IBD.

Understanding the role of the gut microbiota in the pathogenesis of inflammatory bowel diseases (IBD) has been an area of intense research over the past decades. Patients with IBD exhibit alterations in their microbial composition compared to healthy controls. However, studies focusing solely on taxonomic analyses have struggled to deliver replicable findings across cohorts regarding which microbial species drive the distinct patterns in IBD. The focus of research has therefore shifted to studying the functionality of gut microbes, especially by investigating their effector molecules involved in the immunomodulatory functions of the microbiota, namely metabolites. Metabolic profiles are altered in IBD, and several metabolites have been shown to play a causative role in shaping immune functions in animal models. Therefore, understanding the complex communication between the microbiota, metabolites, and the host bears great potential to unlock new biomarkers for diagnosis, disease course and therapy response as well as novel therapeutic options in the treatment of IBD. In this review, we primarily focus on promising classes of metabolites which are thought to exert beneficial effects and are generally decreased in IBD. Though results from human trials are promising, they have not so far provided a large-scale break-through in IBD-therapy improvement. We therefore propose tailored personalized supplementation of microbiota and metabolites based on multi-omics analysis which accounts for the individual microbial and metabolic profiles in IBD patients rather than one-size-fits-all approaches.

Inflammatory Bowel Disease (IBD) is an autoimmune disease characterized by chronic relapsing inflammation of the intestinal tract. Gut microbiota (GM) and CD4+T cells are important in the development of IBD. A lot of studies have shown that GM and their metabolites like short-chain fatty acids, bile acids and tryptophan can be involved in the differentiation of CD4+T cells through various mechanisms, which in turn regulate the immune homeostasis of the IBD patients. Therefore, regulating CD4+T cells through GM may be a potential therapeutic direction for the treatment of IBD. Many studies have shown that Traditional Chinese Medicine (TCM) formulas and some herbal extracts can affect CD4+T cell differentiation by regulating GM and its metabolites. In this review, we mainly focus on the role of GM and their metabolites in regulating the differentiation of CD4+T cells and their correlation with IBD. We also summarize the current research progress on the regulation of this process by TCM.

Integrating artificial intelligence (AI) into clinical trials for inflammatory bowel disease (IBD) has potential to be transformative to the field. This article explores how AI-driven technologies, including machine learning (ML), natural language processing, and predictive analytics, have the potential to enhance important aspects of IBD trials-from patient recruitment and trial design to data analysis and personalized treatment strategies. As AI advances, it has potential to improve long-standing challenges in trial efficiency, accuracy, and personalization with the goal of accelerating the discovery of novel therapies and improve outcomes for people living with IBD. AI can streamline multiple trial phases, from target identification and patient recruitment to data analysis and monitoring. By integrating multi-omics data, electronic health records, and imaging repositories, AI can uncover molecular targets and personalize trial strategies, ultimately expediting drug development. However, the adoption of AI in IBD clinical trials encounters significant challenges. These include technical barriers in data integration, ethical concerns regarding patient privacy, and regulatory issues related to AI validation standards. Additionally, AI models risk producing biased outcomes if training datasets lack diversity, potentially impacting underrepresented populations in clinical trials. Addressing these limitations requires standardized data formats, interdisciplinary collaboration, and robust ethical frameworks to ensure inclusivity and accuracy. Continued partnerships among clinicians, researchers, data scientists, and regulators will be essential to establish transparent, patient-centered AI frameworks. By overcoming these obstacles, AI has the potential to enhance the efficiency, equity, and efficacy of IBD clinical trials, ultimately benefiting patient care.

Gut microbiome changes have been associated with several human diseases, but the molecular and functional details underlying these associations remain largely unknown. Here, we performed a meta-analysis of small molecule biosynthetic gene clusters (BGCs) in metagenomic samples of the gut microbiome from inflammatory bowel disease (IBD) patients and matched healthy subjects and identified two Clostridia-derived BGCs that are significantly associated with Crohn's disease (CD), a main IBD type. Using synthetic biology, we discovered and solved the structures of six fatty acid amides as the products of the CD-enriched BGCs, which we subsequently detected in fecal samples from IBD patients. Finally, we show that the discovered molecules disrupt gut permeability and exacerbate disease in chemically or genetically susceptible mouse models of colitis. These findings suggest that microbiome-derived small molecules may play a role in the etiology of IBD and represent a generalizable approach for discovering molecular mediators of disease-relevant microbiome-host interactions.

Crohn's disease (CD) results from alterations in the gut microbiota and the immune system. However, the exact metabolic dysfunctions of the gut microbiota during CD are still unclear. Here, we investigated metagenomic functions using PICRUSt2 during the course of CD to better understand microbiota-related disease mechanisms and provide new insights for novel therapeutic strategies.

We performed 16S rRNA-based microbial profiling of 567 faecal samples collected from a cohort of 383 CD patients, including 291 remissions (CR), 177 mild-moderate (CM) and 99 severe (CS) disease states. Gene and pathway composition was assessed using PICRUSt2 analyses of 16S data.

As expected, changes in alpha and beta diversity, in interaction networks and increases in Proteobacteria abundance were associated with disease severity. However, microbial function was more consistently disrupted than composition from CR, to CM and then to CS. Major shifts in oxidative stress pathways and reduced carbohydrate and amino acid metabolism in favour of nutrient transport were identified in CS compared to CR. Virulence factors involved in host invasion, host evasion and inflammation were also increased in CS.

This functional metagenomic information provides new insights into community-wide microbial processes and pathways associated with CD pathogenesis. This study paves the way for new advanced strategies to rebalance gut microbiota and/or eliminate oxidative stress, and biofilm to downregulate gut inflammation.

Infection with the COVID-19-causing pathogen SARS-CoV-2 is associated with disruption in the human gut microbiome. The gut microbiome enables protection against diverse pathogens and exhibits dysbiosis during infectious and autoimmune disease. Studies based in the United States and China have found that severe COVID-19 cases have altered gut microbiome composition when compared to mild COVID-19 cases. We present the first study to investigate the gut microbiome composition of COVID-19 cases in a population from Sub-Saharan Africa. Given the impact of geography and cultural traditions on microbiome composition, it is important to investigate the microbiome globally and not draw broad conclusions from homogenous populations.

We used stool samples in a Ugandan biobank collected from COVID-19 cases during 2020-2022. We profiled the gut microbiomes of 83 symptomatic individuals who tested positive for SARS-CoV-2 along with 43 household contacts who did not present any symptoms of COVID-19. The inclusion of healthy controls enables us to generate hypotheses about bacterial strains potentially related to susceptibility to COVID-19 disease, which is highly heterogeneous. Comparison of the COVID-19 patients and their household contacts revealed decreased alpha diversity and blooms of Enterococcus and Eggerthella in COVID-19 cases.

Our study finds that the microbiome of COVID-19 individuals is more likely to be disrupted, as indicated by decreased diversity and increased pathobiont levels. This is either a consequence of the disease or may indicate that certain microbiome states increase susceptibility to COVID-19 disease. Our findings enable comparison with cohorts previously published in the Global North, as well as support new hypotheses about the interaction between the gut microbiome and SARS-CoV-2 infection.

Despite combination antiretroviral therapy (ART), HIV causes persistent gut barrier dysfunction, immune depletion, and dysbiosis. Furthermore, ART interruption results in reservoir reactivation and rebound viremia. Both IL-21 and anti-α4β7 improve gut barrier functions, and we hypothesized that combining them would synergize as a dual therapy to improve immunological outcomes in SIV-infected rhesus macaques (RMs). We found no significant differences in CD4+ T cell reservoir size by intact proviral DNA assay. SIV rebounded in both dual-treated and control RMs following analytical therapy interruption (ATI), with time to rebound and initial rebound viremia comparable between groups; however, dual-treated RMs showed slightly better control of viral replication at the latest time points after ATI. Additionally, following ATI, dual-treated RMs showed immunological benefits, including T cell preservation and lower PD-1+ central memory T cell (TCM) frequency. Notably, PD-1+ TCMs were associated with reservoir size, which predicted viral loads (VLs) after ATI. Finally, 16S rRNA-Seq revealed better recovery from dysbiosis in treated animals, and the butyrate-producing Firmicute Roseburia predicted PD-1-expressing TCMs and VLs after ATI. PD-1+ TCMs and gut dysbiosis represent mechanisms of HIV persistence and pathogenesis, respectively. Therefore, combining IL-21 and anti-α4β7 may be an effective therapeutic strategy to improve immunological outcomes for people with HIV.

Microbiome science has evolved rapidly in the past decade, with high-profile publications suggesting that the gut microbiome is a causal determinant of human health. This has led to the emergence of microbiome-focused biotechnology companies and pharmaceutical company investment in the research and development of gut-derived therapeutics. Despite the early promise of this field, the first generation of microbiome-derived therapeutics (faecal microbiota products) have only recently been approved for clinical use. Next-generation therapies based on readily culturable and as-yet-unculturable colonic bacterial species (with the latter estimated to comprise 63% of all detected species) have not yet progressed to pivotal phase 3 trials. This reflects the many challenges involved in developing a new class of drugs in an evolving field. Here we discuss the evolution of the live biotherapeutics field over the past decade, from the development of first-generation products to the emergence of rationally designed second- and third-generation live biotherapeutics. Finally, we present our outlook for the future of this field.

Despite the success of biological therapies in treating inflammatory bowel disease, managing patients remains challenging due to the absence of reliable predictors of therapy response.

In this study, we prospectively sampled 2 cohorts of patients with inflammatory bowel disease receiving the anti-integrin α4β7 antibody vedolizumab. Samples were subjected to mass cytometry; single-cell RNA sequencing; single-cell B and T cell receptor sequencing (BCR/TCR-seq); serum proteomics; and multiparametric flow cytometry to comprehensively assess vedolizumab-induced immunologic changes in the peripheral blood and their potential associations with treatment response.

Vedolizumab treatment led to substantial alterations in the abundance of circulating immune cell lineages and modified the T-cell receptor diversity of gut-homing CD4+ memory T cells. Through integration of multimodal parameters and machine learning, we identified a significant increase in proliferating CD4+ memory T cells among nonresponders before treatment compared with responders. This predictive T-cell signature demonstrated an activated T-helper 1/T-helper 17 cell phenotype and exhibited elevated levels of integrin α4β1, potentially making these cells less susceptible to direct targeting by vedolizumab.

These findings provide a reliable predictive classifier with significant implications for personalized inflammatory bowel disease management.

Inflammatory bowel disease (IBD) has been considered a relative contraindication to radiation therapy (RT) because of the potential greater risk of RT-induced toxicities. This study aimed to assess acute toxicity outcomes in patients with IBD treated with abdominal/pelvic RT.

After institutional review board approval, patients with IBD who received RT to the abdomen/pelvis were identified from an institutional research repository, and their electronic medical records were reviewed. The IBD cohort was matched 1:1 with controls according to all of the following: RT, gender, disease site, age, and year of RT. Acute toxicity was defined as toxicity occurring within 3 months of RT. Primary outcomes were assessed via univariable logistic regression models and the predicted probability of acute toxicity and acute gastrointestinal (GI) toxicity were plotted for the most significant covariates. IBD and control cohorts were compared on demographic and toxicity variables using χ2/Fisher exact tests and Kruskal-Wallis tests where appropriate.

We identified 62 patients with a median age of 64 years (IQR, 54-70 years) who received RT from 2006 to 2022. Patients were treated with intensity modulated RT (38; 61.3%), 3-dimensional conformal RT (12; 19.4%), and stereotactic body RT/brachytherapy (12; 19.4%). After RT, 28 (45.2%) and 23 (37.1%) patients experienced grade ≥2 acute (any) and acute GI toxicity, respectively. Higher overall RT dose and RT dose to small bowel were found to be significantly associated with increased risk of grade ≥2 acute toxicities (OR, 1.041 per unit Gy; 95% CI, 1.005-1.084; P = .034 and OR, 1.046; 95% CI, 1.018-1.082; P = .003, respectively). Between IBD and control cohorts, there were no significant differences in grade ≥2 acute (any) and acute GI toxicities (P = .710 and P = .704, respectively).

In patients with IBD treated with abdominal/pelvic RT for malignancy, RT was effective and well-tolerated. RT treatment planning should carefully consider the location(s) of IBD inflammation and dose to bowel structures, in particular, dose to the small bowel.

Inflammatory Bowel Disease (IBD), which includes Ulcerative Colitis (UC) and Crohn's Disease (CD), is marked by dysbiosis of the gut microbiome. Despite therapeutic interventions with biological agents like Vedolizumab, Ustekinumab, and anti-TNF agents, the variability in clinical, histological, and molecular responses remains significant due to inter-individual and inter-population differences. This study introduces a novel approach using Individual Specific Networks (ISNs) derived from faecal microbial measurements of IBD patients across multiple cohorts. These ISNs, constructed from baseline and follow-up data post-treatment, successfully predict therapeutic outcomes based on endoscopic remission criteria. Our analysis revealed that ISNs characterised by core gut microbial families, including Lachnospiraceae and Ruminococcaceae, are predictive of treatment responses. We identified significant changes in abundance levels of specific bacterial genera in response to treatment, confirming the robustness of ISNs in capturing both linear and non-linear microbiota signals. Utilising network topological metrics, we further validated these findings, demonstrating that critical microbial features identified through ISNs can differentiate responders from non-responders with respect to various therapeutic outcomes. The study highlights the potential of ISNs to provide individualised insights into microbiota-driven therapeutic responses, emphasising the need for larger cohort studies to enhance the accuracy of molecular biomarkers. This innovative methodology paves the way for more personalised and effective treatment strategies in managing IBD.

The emergence of Next Generation Sequencing (NGS) technology has catalyzed a paradigm shift in clinical diagnostics and personalized medicine, enabling unprecedented access to high-throughput microbiome data. However, the inherent high dimensionality, noise, and variability of microbiome data present substantial obstacles to conventional statistical methods and machine learning techniques. Even the promising deep learning (DL) methods are not immune to these challenges. This paper introduces a novel feature engineering method that circumvents these limitations by amalgamating two feature sets derived from input data to generate a new dataset, which is then subjected to feature selection. This innovative approach markedly enhances the Area Under the Curve (AUC) performance of the Deep Neural Network (DNN) algorithm in colorectal cancer (CRC) detection using gut microbiome data, elevating it from 0.800 to 0.923. The proposed method constitutes a significant advancement in the field, providing a robust solution to the intricacies of microbiome data analysis and amplifying the potential of DL methods in disease detection.

Ulcerative colitis is a chronic inflammatory condition of the colon driven by aberrant immune activation. Although advanced medical therapies form the cornerstone of ulcerative colitis management, unmet needs include failure to induce and sustain remission in a substantial proportion of patients and in managing acute severe ulcerative colitis. We review new treatment strategies that might improve patient outcomes in the management of moderate-to-severe ulcerative colitis.

A literature search was conducted using the PubMed database, including studies published from inception to October 2024, selected for their relevance. Recognizing current limitations, this article reviews strategies to improve treatment outcomes in ulcerative colitis using advanced therapies. These approaches include early treatment initiation, dose optimization, positioning newer agents as first-line therapies, combination therapy, targeting novel therapeutic endpoints, and the management of acute severe ulcerative colitis.

The strategies discussed may contribute to establishing new standards of care aimed at achieving long-term remission and enhancing patient outcomes. Personalized therapy, which tailors treatment based on individual disease characteristics and risk factors, is anticipated to become a critical aspect of delivering more effective care in the future.

The gut microbiota, a complex community of microorganisms, plays a crucial role in gastrointestinal (GI) health, influencing digestion, metabolism, immune function, and the gut-brain axis. Dysbiosis, or an imbalance in microbiota composition, is associated with GI disorders, including irritable bowel syndrome (IBS), inflammatory bowel disease (IBD), and colorectal cancer (CRC). Conventional microbiota analysis methods, such as next-generation sequencing (NGS) and nuclear magnetic resonance (NMR), provide valuable insights but are often expensive, time-consuming, and destructive. Raman spectroscopy (RS) is a non-invasive, cost-effective, and highly sensitive alternative. This analytical technique relies on inelastic light scattering to generate molecular "fingerprints", enabling real-time, marker-free analysis of microbiota composition and metabolic activity. This review explores the principles, sample preparation techniques, and advancements in RS, including surface-enhanced Raman spectroscopy (SERS), for microbiota research. RS facilitates identifying microbial species, analysing key metabolites like short-chain fatty acids (SCFA), and monitoring microbiota responses to dietary and therapeutic interventions. The comparative analysis highlights RS's advantages over conventional techniques, such as the minimal sample preparation, real-time capabilities, and non-destructive nature. The integration of RS with machine learning enhances its diagnostic potential, enabling biomarker discovery and personalised treatment strategies for GI disorders. Challenges, including weak Raman signals and spectral complexity, are discussed alongside emerging solutions. As RS technology advances, mainly through portable spectrometers and AI integration, its clinical application in microbiota diagnostics and personalised medicine is poised to transform GI healthcare, bridging microbiota research with practical therapeutic strategies.

The term "gut microbiota" primarily refers to the ecological community of various microorganisms in the gut, which constitutes the largest microbial community in the human body. Although adequate bowel preparation can improve the results of colonoscopy, it may interfere with the gut microbiota. Bowel preparation for colonoscopy can lead to transient changes in the gut microbiota, potentially affecting an individual's health, especially in vulnerable populations, such as patients with inflammatory bowel disease. However, measures such as oral probiotics may ameliorate these adverse effects. We focused on the bowel preparation-induced changes in the gut microbiota and host health status, hypothesized the factors influencing these changes, and attempted to identify measures that may reduce dysbiosis, thereby providing more information for individualized bowel preparation for colonoscopy in the future.

Immunotherapy-related colitis (irC) frequently emerges as an immune-related adverse event during immune checkpoint inhibitor therapy and is presumably influenced by the gut microbiota. We longitudinally studied microbiomes from 38 ICI-treated cancer patients. We compared 13 ICI-treated subjects who developed irC against 25 ICI-treated subjects who remained irC-free, along with a validation cohort. Leveraging a preclinical mouse model, predisease stools from irC subjects induced greater colitigenicity upon transfer to mice. The microbiota during the first 10 days of irC closely resembled inflammatory bowel disease microbiomes, with reduced diversity, increased Proteobacteria and Veillonella, and decreased Faecalibacterium, which normalized before irC remission. These findings highlight the irC gut microbiota as functionally distinct but phylogenetically similar to non-irC and healthy microbiomes, with the exception of an acute, transient disruption early in irC. We underscore the significance of longitudinal microbiome profiling in developing clinical avenues to detect, monitor, and mitigate irC in ICI therapy cancer patients.

The gut microbiota plays a pivotal role in ulcerative colitis (UC) development. This study explores the impact of latent tuberculosis infection (LTBI) on the gut microbiota in UC and assesses changes during vedolizumab treatment, investigating prophylactic anti-tuberculosis therapy.

This cohort study included adult patients with UC receiving vedolizumab treatment at Jinhua Hospital, Zhejiang University from April 2021 to December 2022. Patients were divided into LTBI (n = 24) and non-LTBI (n = 21) groups. Patients in the LTBI group were further subdivided into prophylactic (n = 13) and non-prophylactic (n = 11) groups. Clinical and fecal samples were collected pre- and post-vedolizumab treatment for the LTBI groups and pre-treatment for the non-LTBI group. The gut microbiota was analyzed using 16 S rRNA sequencing. Patients in the non-LTBI group exhibited higher diversity indices. Vedolizumab demonstrated efficacy in the LTBI group, with clinical response and remission rates of 83.3% and 75.0%, respectively. The gut microbiota diversity in the LTBI group increased post-vedolizumab treatment, and receiving prophylactic isoniazid showed no significant difference in vedolizumab treatment response compared to not receiving prophylactic isoniazid. Microbiota changes were similar between groups, with an increase in [Ruminococcus] expression after vedolizumab treatment.

This cohort study, conducted at a single center, highlights that LTBI can reduce gut microbiota diversity among adult patient with UC. The observed efficacy of vedolizumab treatment in the LTBI group indicates a potential association with microbiota changes. However, mono-isoniazid exhibited limited impact, underscoring the potential of vedolizumab as a promising candidate for prophylactic anti-tuberculosis treatment in the context of UC.

Developing microbiome-based markers for pediatric inflammatory bowel disease (PIBD) is challenging. Here, we evaluated the diagnostic and prognostic potential of the gut microbiome in PIBD through a case-control study and cross-cohort analyses. In a Korean PIBD cohort (24 patients with PIBD, 43 controls), we observed that microbial diversity and composition shifted in patients with active PIBD versus controls and recovered at remission. We employed a differential abundance meta-analysis approach to identify microbial markers consistently associated with active inflammation and remission across seven PIBD cohorts from six countries (n = 1,670) including our dataset. Finally, we trained and tested various machine learning models for their ability to predict a patient's future remission based on baseline bacterial composition. An ensemble model trained with the amplicon sequence variants effectively predicted future remission of PIBD. This research highlights the gut microbiome's potential to guide precision therapy for PIBD.

Human Immunodeficiency Virus (HIV)/Simian Immunodeficiency Virus (SIV) infection is associated with significant gut damage, similar to that observed in patients with inflammatory bowel disease (IBD). This pathology includes loss of epithelial integrity, microbial translocation, dysbiosis, and resultant chronic immune activation. Additionally, the levels of all-trans-retinoic acid (atRA) are dramatically attenuated. Data on the therapeutic use of anti-α4β7 antibodies has shown promise in patients with ulcerative colitis and Crohn's disease. Recent evidence has suggested that the microbiome and short-chain fatty acid (SCFA) metabolites it generates may be critical for anti-α4β7 efficacy and maintaining intestinal homeostasis.

To determine whether the microbiome contributes to gut homeostasis after anti-α4β7 antibody administered to SIV-infected rhesus macaques, faecal SCFA concentrations were determined, 16S rRNA sequencing was performed, plasma viral loads were determined, plasma retinoids were measured longitudinally, and gut retinoid synthesis/response gene expression was quantified.

Our results suggest that anti-α4β7 antibody facilitates the return of retinoid metabolism to baseline levels after SIV infection. Furthermore, faecal SCFAs were shown to be associated with retinoid synthesis gene expression and rebound viral loads after therapy interruption.

Taken together, these data demonstrate the therapeutic advantages of anti-α4β7 antibody administration during HIV/SIV infection and that the efficacy of anti-α4β7 antibody may depend on microbiome composition and SCFA generation.

The development of multi-omics technologies has generated an abundance of biological datasets, providing valuable resources for investigating potential relationships within complex biological systems. However, most correlation analysis tools face computational challenges when dealing with these high-dimensional datasets containing millions of features. Here, we introduce pyNetCor, a fast and scalable tool for constructing correlation networks on large-scale and high-dimensional data. PyNetCor features optimized algorithms for both full correlation coefficient matrix computation and top-k correlation search, outperforming other tools in the field in terms of runtime and memory consumption. It utilizes a linear interpolation strategy to rapidly estimate P-values and achieve false discovery rate control, demonstrating a speedup of over 110 times compared to existing methods. Overall, pyNetCor supports large-scale correlation analysis, a crucial foundational step for various bioinformatics workflows, and can be easily integrated into downstream applications to accelerate the process of extracting biological insights from data.

Various extrinsic and intrinsic factors such as drug exposures, antibiotic treatments, smoking, lifestyle, genetics, immune responses, and the gut microbiome characterize ulcerative colitis and Crohn's disease, collectively called inflammatory bowel disease (IBD). All these factors contribute to the complexity and heterogeneity of the disease etiology and pathogenesis leading to major challenges for the scientific community in improving management, medical treatments, genetic risk, and exposome impact. Understanding the interaction(s) among these factors and their effects on the immune system in IBD patients has prompted advances in multi-omics research, the development of new tools as part of system biology, and more recently, artificial intelligence (AI) approaches. These innovative approaches, supported by the availability of big data and large volumes of digital medical datasets, hold promise in better understanding the natural histories, predictors of disease development, severity, complications and treatment outcomes in complex diseases, providing decision support to doctors, and promising to bring us closer to the realization of the "precision medicine" paradigm. This review aims to provide an overview of current IBD omics based on both individual (genomics, transcriptomics, proteomics, metagenomics) and multi-omics levels, highlighting how AI can facilitate the integration of heterogeneous data to summarize our current understanding of the disease and to identify current gaps in knowledge to inform upcoming research in this field.

The gut microbiota is crucial for human health, functioning as a complex adaptive system akin to a vital organ. To identify core health-relevant gut microbes, we followed the systems biology tenet that stable relationships signify core components. By analyzing metagenomic datasets from a high-fiber dietary intervention in type 2 diabetes and 26 case-control studies across 15 diseases, we identified a set of stably correlated genome pairs within co-abundance networks perturbed by dietary interventions and diseases. These genomes formed a "two competing guilds" (TCGs) model, with one guild specialized in fiber fermentation and butyrate production and the other characterized by virulence and antibiotic resistance. Our random forest models successfully distinguished cases from controls across multiple diseases and predicted immunotherapy outcomes through the use of these genomes. Our guild-based approach, which is genome specific, database independent, and interaction focused, identifies a core microbiome signature that serves as a holistic health indicator and a potential common target for health enhancement.

We would like to present some new thoughts on the publication in the journal published in August 2024 in World Journal of Gastroenterology. We specifically focused on the alterations in the intestinal tract, mesenteric adipose tissue (MAT), and systemic inflammatory changes in mice following fecal flora transplantation into a mouse model of Crohn's disease (CD). Accumulating evidence suggests that the occurrence of CD is influenced by environmental factors, host immune status, genetic susceptibility, and flora imbalance. One microbiota-based intervention, fecal microbiota transplantation, has emerged as a potential treatment option for CD. The MAT is considered a "second barrier" around the inflamed intestine. The interaction between gut microbes and inflammatory changes in MAT has attracted considerable interest. In the study under discussion, the authors transplanted fetal fecal microorganisms from patients with CD and clinically healthy donors, respectively, into 2,4,6-trinitrobenzene sulfonic acid-induced CD mice. The research explored the complex interplay between MAT, creeping fat, inflammation, and intestinal flora in CD by evaluating intestinal and mesenteric lesions, along with the systemic inflammatory state in the mice. This article provides several important insights. First, the transplantation of intestinal flora holds significant potential as a therapeutic strategy for CD, offering hope for patients with CD. Second, it presents a novel approach to the diagnosis and treatment of CD: The inflammatory response in CD could potentially be assessed through pathological or imaging changes in the MAT, and CD could be treated by targeting the inflammation of the MAT.

The gut microbiota contributes to aberrant inflammation in inflammatory bowel disease, but the bacterial factors causing or exacerbating inflammation are not fully understood. Further, the predictive or prognostic value of gut microbial biomarkers for remission in response to biologic therapy is unclear.

We perform whole metagenomic sequencing of 550 stool samples from 287 ulcerative colitis patients from a large, phase 3, head-to-head study of infliximab and etrolizumab.

We identify several bacterial species in baseline and/or post-treatment samples that associate with clinical remission. These include previously described associations [Faecalibacterium prausnitzii_F] as well as new associations with remission to biologic therapy [Flavonifractor plautii]. We build multivariate models and find that gut microbial species are better predictors for remission than clinical variables alone. Finally, we describe patient groups that differ in microbiome composition and remission rate after induction therapy, suggesting the potential utility of microbiome-based endotyping.

In this large study of ulcerative colitis patients, we show that few individual species associate strongly with clinical remission, but multivariate models including microbiome can predict clinical remission and have better predictive power compared with clinical data alone.

The mammalian intestine is colonized by trillions of microorganisms that are collectively referred to as the gut microbiota. The majority of symbionts have co-evolved with their host in a mutualistic relationship that benefits both. Under certain conditions, such as in Crohn's disease, a subtype of inflammatory bowel disease, some symbionts bloom to cause disease in genetically susceptible hosts. Although the identity and function of disease-causing microorganisms or pathobionts in Crohn's disease remain largely unknown, mounting evidence from animal models suggests that pathobionts triggering Crohn's disease-like colitis inhabit certain niches and penetrate the intestinal tissue to trigger inflammation. In this Review, we discuss the distinct niches occupied by intestinal symbionts and the evidence that pathobionts triggering Crohn's disease live in the mucus layer or near the intestinal epithelium. We also discuss how Crohn's disease-associated mutations in the host disrupt intestinal homeostasis by promoting the penetration and accumulation of pathobionts in the intestinal tissue. Finally, we discuss the potential role of microbiome-based interventions in precision therapeutic strategies for the treatment of Crohn's disease.

We investigated relationships between disease activity measures and the gut microbiome in children with Crohn's disease (CD) and how these were confounded by gastrointestinal transit time.

Microbiome was profiled (16S rRNA sequencing) in feces from 196 children with CD. Sixty participants also provided samples after 18 months. Mural inflammation (Pediatric Inflammatory Crohn's Magnetic Resonance Enterography Index, PICMI), the simple endoscopic score for CD, and the weighted pediatric Crohn's disease activity index (wPCDAI) were assessed. Fecal calprotectin, plasma C-reactive protein (CRP), and fecal water content (FWC), a proxy of gastrointestinal transit time, were measured too.

Microbiome α diversity, clustering, and differential taxa were related to disease status, but varied remarkably by disease activity measure used. The strongest relationships between microbiome and disease activity status were observed using wPCDAI; fewer or no relationships were seen using more objective measures like PICMI. Taxa predictive of disease activity status were dependent on the disease activity measure used with negligible overlap. Active disease was associated with more pathobionts (eg, Viellonella, Enterobacterales) and fewer fiber-fermenting organisms. The effect FWC had on microbiome superseded the effect of active disease for all disease activity measures, particularly with wPCDAI. Accounting for FWC, the differences in microbial signatures explained by disease activity status were attenuated or lost.

In CD, microbiome signatures fluctuate depending on the measure used to assess disease severity; several of these signals might be secondary disease effects linked with changes in gut motility in active disease. PICMI appears to be less influenced when studying relationships between microbiome and mural inflammation in CD.

Colorectal cancer (CRC) arises from aberrant mutations in colorectal cells, frequently linked to chronic inflammation. This study integrated human gut metagenome analysis with an azoxymethane and dextran sulfate sodium-induced CRC mouse model to investigate the dynamics of inflammation, gut microbiota, and metabolomic profiles throughout tumorigenesis. The analysis of stool metagenome data from 30 healthy individuals and 40 CRC patients disclosed a significant escalation in both gut microbiota diversity and abundance in CRC patients compared to healthy individuals (p < 0.05). Marked structural disparities were identified between the gut microbiota of healthy individuals and those with CRC (p < 0.05), characterized by elevated levels of clostridia and diminished bifidobacteria in CRC patients (p < 0.05). In the mouse model, CRC mice exhibited distinct gut microbiota structures and metabolite signatures at early and advanced tumor stages, with subtle variations noted during the intermediate phase. Additionally, inflammatory marker levels increased progressively during tumor development in CRC mice, in contrast to their stable levels in healthy counterparts. These findings suggest that persistent inflammation might precipitate gut dysbiosis and altered microbial metabolism. Collectively, this study provides insights into the interplay between inflammation, gut microbiota, and metabolite changes during CRC progression, offering potential biomarkers for diagnosis. While further validation with larger cohorts is warranted, the data obtained support the development of CRC prevention and diagnosis strategies.