The distinct features of microbial 'dysbiosis' of Crohn's disease do not occur to the same extent in their unaffected, genetically-linked kindred

Persistent dysbiosis of duodenal microbiota in patients with controlled pediatric Crohn's disease after resolution of inflammation

Crohn's disease is an inflammatory condition of the intestine characterized by largely unknown etiology and a relapse remission cycle of disease control. While possible triggers have been identified, research is inconsistent on the precise cause of these relapses, especially in the under-researched pediatric population. We hypothesized that patients in remission would have persistent microbial and inflammatory changes in small intestinal tissue that might trigger relapse. To this end, we analyzed intestinal biopsy samples from six patients with pediatric Crohn's disease in remission and a control group of 16 pediatric patients with no evident pathogenic abnormality. We identified compositional microbiota differences, including decreases in the genera Streptococcus and Actinobacillus as well as increases in Oribacterium and Prevotella in patients with controlled Crohn's disease compared to controls. Further, a histologic analysis found that patients with controlled Crohn's disease had increased epithelial integrity, and decreased intraepithelial lymphocytes compared with controls. Additionally, we observed increased peripheral CD4+ T cells in patients with pediatric Crohn's disease. These results indicate that markers of intestinal inflammation are responsive to Crohn's disease treatment, however the interventions may not resolve the underlying dysbiosis. These findings suggest that persistent dysbiosis may increase vulnerability to relapse of pediatric Crohn's disease. This study used a nested cohort of patients from the Bangladesh Environmental Enteric Dysfunction (BEED) study (ClinicalTrials.gov ID: NCT02812615 Date of first registration: 24/06/2016).

Comparison of the effectiveness of different normalization methods for metagenomic cross-study phenotype prediction under heterogeneity

The human microbiome, comprising microorganisms residing within and on the human body, plays a crucial role in various physiological processes and has been linked to numerous diseases. To analyze microbiome data, it is essential to account for inherent heterogeneity and variability across samples. Normalization methods have been proposed to mitigate these variations and enhance comparability. However, the performance of these methods in predicting binary phenotypes remains understudied. This study systematically evaluates different normalization methods in microbiome data analysis and their impact on disease prediction. Our findings highlight the strengths and limitations of scaling, compositional data analysis, transformation, and batch correction methods. Scaling methods like TMM show consistent performance, while compositional data analysis methods exhibit mixed results. Transformation methods, such as Blom and NPN, demonstrate promise in capturing complex associations. Batch correction methods, including BMC and Limma, consistently outperform other approaches. However, the influence of normalization methods is constrained by population effects, disease effects, and batch effects. These results provide insights for selecting appropriate normalization approaches in microbiome research, improving predictive models, and advancing personalized medicine. Future research should explore larger and more diverse datasets and develop tailored normalization strategies for microbiome data analysis.

Gut microbiota signatures in inflammatory bowel disease

BACKGROUND

Inflammatory bowel diseases (IBD), including Crohn's disease (CD) and ulcerative colitis (UC), affect millions of people worldwide with increasing incidence.

OBJECTIVES

Several studies have shown a link between gut microbiota composition and IBD, but results are often limited by small sample sizes. We aimed to re-analyze publicly available fecal microbiota data from IBD patients.

METHODS

We extracted original fecal 16S rRNA amplicon sequencing data from 45 cohorts of IBD patients and healthy individuals using the BioProject database at the National Center for Biotechnology Information. Unlike previous meta-analyses, we merged all study cohorts into a single dataset, including sex, age, geography, and disease information, based on which microbiota signatures were analyzed, while accounting for varying technical platforms.

RESULTS

Among 2518 individuals in the combined dataset, we discovered a hitherto unseen number of genera associated with IBD. A total of 77 genera associated with CD, of which 38 were novel associations, and a total of 64 genera associated with UC, of which 28 represented novel associations. Signatures were robust across different technical platforms and geographic locations. Reduced alpha diversity in IBD compared to healthy individuals, in CD compared to UC, and altered microbiota composition (beta diversity) in UC and especially in CD as compared to healthy individuals were found.

CONCLUSIONS

Combining original microbiota data from 45 cohorts, we identified a hitherto unseen large number of genera associated with IBD. Identification of microbiota features robustly associated with CD and UC may pave the way for the identification of new treatment targets.

GDmicro: classifying host disease status with GCN and deep adaptation network based on the human gut microbiome data

MOTIVATION

With advances in metagenomic sequencing technologies, there are accumulating studies revealing the associations between the human gut microbiome and some human diseases. These associations shed light on using gut microbiome data to distinguish case and control samples of a specific disease, which is also called host disease status classification. Importantly, using learning-based models to distinguish the disease and control samples is expected to identify important biomarkers more accurately than abundance-based statistical analysis. However, available tools have not fully addressed two challenges associated with this task: limited labeled microbiome data and decreased accuracy in cross-studies. The confounding factors, such as the diet, technical biases in sample collection/sequencing across different studies/cohorts often jeopardize the generalization of the learning model.

RESULTS

To address these challenges, we develop a new tool GDmicro, which combines semi-supervised learning and domain adaptation to achieve a more generalized model using limited labeled samples. We evaluated GDmicro on human gut microbiome data from 11 cohorts covering 5 different diseases. The results show that GDmicro has better performance and robustness than state-of-the-art tools. In particular, it improves the AUC from 0.783 to 0.949 in identifying inflammatory bowel disease. Furthermore, GDmicro can identify potential biomarkers with greater accuracy than abundance-based statistical analysis methods. It also reveals the contribution of these biomarkers to the host's disease status.

AVAILABILITY AND IMPLEMENTATION

https://github.com/liaoherui/GDmicro.

Achieving pan-microbiome biological insights via the dbBact knowledge base

16S rRNA amplicon sequencing provides a relatively inexpensive culture-independent method for studying microbial communities. Although thousands of such studies have examined diverse habitats, it is difficult for researchers to use this vast trove of experiments when interpreting their own findings in a broader context. To bridge this gap, we introduce dbBact - a novel pan-microbiome resource. dbBact combines manually curated information from studies across diverse habitats, creating a collaborative central repository of 16S rRNA amplicon sequence variants (ASVs), which are assigned multiple ontology-based terms. To date dbBact contains information from more than 1000 studies, which include 1500000 associations between 360000 ASVs and 6500 ontology terms. Importantly, dbBact offers a set of computational tools allowing users to easily query their own datasets against the database. To demonstrate how dbBact augments standard microbiome analysis we selected 16 published papers, and reanalyzed their data via dbBact. We uncovered novel inter-host similarities, potential intra-host sources of bacteria, commonalities across different diseases and lower host-specificity in disease-associated bacteria. We also demonstrate the ability to detect environmental sources, reagent-borne contaminants, and identify potential cross-sample contaminations. These analyses demonstrate how combining information across multiple studies and over diverse habitats leads to better understanding of underlying biological processes.

Identifying Microbiome Dynamics in Pediatric IBD: More than a Family Matter

BACKGROUND

Pediatric inflammatory bowel disease (IBD) is a chronic inflammatory intestinal disease that affects both children and adolescents. Symptoms can significantly affect a child's growth, development, and quality of life, making early diagnosis and effective management crucial. This study focuses on treatment-naïve pediatric IBD patients and their immediate families to identify the role of the microbiome in disease onset.

METHODS

Nine families with pediatric IBD were recruited, comprising seven drug-naïve Crohn's disease (CD) patients and two drug-naïve ulcerative colitis (UC) patients, as well as twenty-four healthy siblings/parents. Fecal samples were collected for 16S ribosomal RNA gene sequencing and bioinformatics analysis.

RESULTS

We identified patterns of dysbiosis and hallmark microbial taxa among patients who shared ethnic, habitual, and dietary traits with themselves and their families. In addition, we examined the impact of the disease on specific microbial taxa and how these could serve as potential biomarkers for early detection.

CONCLUSIONS

Our results suggest a potential role of maternal factors in the establishment and modulation of the early life microbiome, consistent with the current literature, which may have implications for understanding the etiology and progression of IBD.

A shared mucosal gut microbiota signature in primary sclerosing cholangitis before and after liver transplantation

BACKGROUND AND AIMS

Several characteristic features of the fecal microbiota have been described in primary sclerosing cholangitis (PSC), whereas data on mucosal microbiota are less consistent. We aimed to use a large colonoscopy cohort to investigate key knowledge gaps, including the role of gut microbiota in PSC with inflammatory bowel disease (IBD), the effect of liver transplantation (LT), and whether recurrent PSC (rPSC) may be used to define consistent microbiota features in PSC irrespective of LT.

APPROACH AND RESULTS

We included 84 PSC and 51 liver transplanted PSC patients (PSC-LT) and 40 healthy controls (HCs) and performed sequencing of the 16S ribosomal RNA gene (V3-V4) from ileocolonic biopsies. Intraindividual microbial diversity was reduced in both PSC and PSC-LT versus HCs. An expansion of Proteobacteria was more pronounced in PSC-LT (up to 19% relative abundance) than in PSC (up to 11%) and HCs (up to 8%; Q FDR  < 0.05). When investigating PSC before (PSC vs. HC) and after LT (rPSC vs. no-rPSC), increased variability (dispersion) in the PSC group was found. Five genera were associated with PSC before and after LT. A dysbiosis index calculated from the five genera, and the presence of the potential pathobiont, Klebsiella , were associated with reduced LT-free survival. Concomitant IBD was associated with reduced Akkermansia .

CONCLUSIONS

Consistent mucosal microbiota features associated with PSC, PSC-IBD, and disease severity, irrespective of LT status, highlight the usefulness of investigating PSC and rPSC in parallel, and suggest that the impact of gut microbiota on posttransplant liver health should be investigated further.

Analysis of pit latrine microbiota reveals depth-related variation in composition, and key parameters and taxa associated with latrine fill-up rate

Pit latrines are used by billions of people globally, often in developing countries where they provide a low-tech and low-cost sanitation method. However, health and social problems can arise from a lack of emptying or maintenance of these facilities. A better understanding of the biological and environmental parameters within pit latrines could inform attempts to enhance material decomposition rates, and therefore slow fill-up rate. In this study, we have performed a spatial analysis of 35 Tanzanian pit latrines to identify bacteria and environmental factors that are associated with faster or slower pit latrine fill-up rates. Using ordination of microbial community data, we observed a linear gradient in terms of beta diversity with increasing pit latrine sample depth, corresponding to a shift in microbial community structure from gut-associated families in the top layer to environmental- and wastewater-associated taxa at greater depths. We also investigated the bacteria and environmental parameters associated with fill-up rates, and identified pH, volatile solids, and volatile fatty acids as features strongly positively correlated with pit latrine fill-up rates, whereas phosphate was strongly negatively correlated with fill-up rate. A number of pit latrine microbiota taxa were also correlated with fill-up rates. Using a multivariate regression, we identified the Lactobacillaceae and Incertae_Sedis_XIII taxa as particularly strongly positively and negatively correlated with fill-up rate, respectively. This study therefore increases knowledge of the microbiota within pit latrines, and identifies potentially important bacteria and environmental variables associated with fill-up rates. These new insights may be useful for future studies investigating the decomposition process within pit latrines.

Successful Dietary Therapy in Paediatric Crohn's Disease is Associated with Shifts in Bacterial Dysbiosis and Inflammatory Metabotype Towards Healthy Controls

BACKGROUND AND AIMS

Nutritional therapy with the Crohn's Disease Exclusion Diet + Partial Enteral Nutrition [CDED+PEN] or Exclusive Enteral Nutrition [EEN] induces remission and reduces inflammation in mild-to-moderate paediatric Crohn's disease [CD]. We aimed to assess if reaching remission with nutritional therapy is mediated by correcting compositional or functional dysbiosis.

METHODS

We assessed metagenome sequences, short chain fatty acids [SCFA] and bile acids [BA] in 54 paediatric CD patients reaching remission after nutritional therapy [with CDED + PEN or EEN] [NCT01728870], compared to 26 paediatric healthy controls.

RESULTS

Successful dietary therapy decreased the relative abundance of Proteobacteria and increased Firmicutes towards healthy controls. CD patients possessed a mixture of two metabotypes [M1 and M2], whereas all healthy controls had metabotype M1. M1 was characterised by high Bacteroidetes and Firmicutes, low Proteobacteria, and higher SCFA synthesis pathways, and M2 was associated with high Proteobacteria and genes involved in SCFA degradation. M1 contribution increased during diet: 48%, 63%, up to 74% [Weeks 0, 6, 12, respectively.]. By Week 12, genera from Proteobacteria reached relative abundance levels of healthy controls with the exception of E. coli. Despite an increase in SCFA synthesis pathways, remission was not associated with increased SCFAs. Primary BA decreased with EEN but not with CDED+PEN, and secondary BA did not change during diet.

CONCLUSION

Successful dietary therapy induced correction of both compositional and functional dysbiosis. However, 12 weeks of diet was not enough to achieve complete correction of dysbiosis. Our data suggests that composition and metabotype are important and change quickly during the early clinical response to dietary intervention. Correction of dysbiosis may therefore be an important future treatment goal for CD.

Host phenotype classification from human microbiome data is mainly driven by the presence of microbial taxa

Machine learning-based classification approaches are widely used to predict host phenotypes from microbiome data. Classifiers are typically employed by considering operational taxonomic units or relative abundance profiles as input features. Such types of data are intrinsically sparse, which opens the opportunity to make predictions from the presence/absence rather than the relative abundance of microbial taxa. This also poses the question whether it is the presence rather than the abundance of particular taxa to be relevant for discrimination purposes, an aspect that has been so far overlooked in the literature. In this paper, we aim at filling this gap by performing a meta-analysis on 4,128 publicly available metagenomes associated with multiple case-control studies. At species-level taxonomic resolution, we show that it is the presence rather than the relative abundance of specific microbial taxa to be important when building classification models. Such findings are robust to the choice of the classifier and confirmed by statistical tests applied to identifying differentially abundant/present taxa. Results are further confirmed at coarser taxonomic resolutions and validated on 4,026 additional 16S rRNA samples coming from 30 public case-control studies.

The composition of the human microbiome has been linked to a large number of different diseases. In this context, classification methodologies based on machine learning approaches have represented a promising tool for diagnostic purposes from metagenomics data. The link between microbial population composition and host phenotypes has been usually performed by considering taxonomic profiles represented by relative abundances of microbial species. In this study, we show that it is more the presence rather than the relative abundance of microbial taxa to be relevant to maximize classification accuracy. This is accomplished by conducting a meta-analysis on more than 4,000 shotgun metagenomes coming from 25 case-control studies and in which original relative abundance data are degraded to presence/absence profiles. Findings are also extended to 16S rRNA data and advance the research field in building prediction models directly from human microbiome data.

Deciphering Active Prophages from Metagenomes

Temperate phages (prophages) are ubiquitous in nature and persist as dormant components of host cells (lysogenic stage) before activating and lysing the host (lytic stage). Actively replicating prophages contribute to central community processes, such as enabling bacterial virulence, manipulating biogeochemical cycling, and driving microbial community diversification. Recent advances in sequencing technology have allowed for the identification and characterization of diverse phages, yet no approaches currently exist for identifying if a prophage has activated. Here, we present PropagAtE (Prophage Activity Estimator), an automated software tool for estimating if a prophage is in the lytic or lysogenic stage of infection. PropagAtE uses statistical analyses of prophage-to-host read coverage ratios to decipher actively replicating prophages, irrespective of whether prophages were induced or spontaneously activated. We demonstrate that PropagAtE is fast, accurate, and sensitive, regardless of sequencing depth. Application of PropagAtE to prophages from 348 complex metagenomes from human gut, murine gut, and soil environments identified distinct spatial and temporal prophage activation signatures, with the highest proportion of active prophages in murine gut samples. In infants treated with antibiotics or infants without treatment, we identified active prophage populations correlated with specific treatment groups. Within time series samples from the human gut, 11 prophage populations, some encoding the sulfur metabolism gene cysH or a rhuM-like virulence factor, were consistently present over time but not active. Overall, PropagAtE will facilitate accurate representations of viruses in microbiomes by associating prophages with their active roles in shaping microbial communities in nature.

IMPORTANCE Viruses that infect bacteria are key components of microbiomes and ecosystems. They can kill and manipulate microorganisms, drive planetary-scale processes and biogeochemical cycling, and influence the structures of entire food networks. Prophages are viruses that can exist in a dormant state within the genome of their host (lysogenic stage) before activating in order to replicate and kill the host (lytic stage). Recent advances have allowed for the identification of diverse viruses in nature, but no approaches exist for characterizing prophages and their stages of infection (prophage activity). We develop and benchmark an automated approach, PropagAtE, to identify the stages of infection of prophages from genomic data. We provide evidence that active prophages vary in identity and abundance across multiple environments and scales. Our approach will enable accurate and unbiased analyses of viruses in microbiomes and ecosystems.

Meta-analysis defines predominant shared microbial responses in various diseases and a specific inflammatory bowel disease signal

BACKGROUND

Gut microbial alteration is implicated in inflammatory bowel disease but is noted in other diseases. Systematic comparison to define similarities and specificities is hampered since most studies focus on a single disease.

RESULTS

We develop a pipeline to compare between disease cohorts starting from the raw V4 16S amplicon sequence variants. Including 12,838 subjects, from 59 disease cohorts, we demonstrate a predominant shared signature across diseases, indicating a common bacterial response to different diseases. We show that classifiers trained on one disease cohort predict relatively well other diseases due to this shared signal, and hence, caution should be taken when using such classifiers in real-world scenarios, where diseases are intermixed. Based on this common signature across a large array of diseases, we develop a universal dysbiosis index that successfully differentiates between cases and controls across various diseases and can be used for prioritizing fecal donors and samples with lower disease probability. Finally, we identify a set of IBD-specific bacteria, which can direct mechanistic studies and design of IBD-specific microbial interventions.

CONCLUSIONS

A robust non-specific general response of the gut microbiome is detected in a large array of diseases. Disease classifiers may confuse between different diseases due to this shared microbial response. Our universal dysbiosis index can be used as a tool to prioritize fecal samples and donors. Finally, the IBD-specific taxa may indicate a more direct association to gut inflammation and disease pathogenesis, and those can be further used as biomarkers and as future targets for interventions.

Therapeutic Advances in Gut Microbiome Modulation in Patients with Inflammatory Bowel Disease from Pediatrics to Adulthood

There is mounting evidence that the gut microbiota plays an important role in the pathogenesis of inflammatory bowel disease (IBD). For the past decade, high throughput sequencing-based gut microbiome research has identified characteristic shifts in the composition of the intestinal microbiota in patients with IBD, suggesting that IBD results from alterations in the interactions between intestinal microbes and the host’s mucosal immune system. These studies have been the impetus for the development of new therapeutic approaches targeting the gut microbiome, such as nutritional therapies, probiotics, fecal microbiota transplant and beneficial metabolic derivatives. Innovative technologies can further our understanding of the role the microbiome plays as well as help to evaluate how the different approaches in microbiome modulation impact clinical responses in adult and pediatric patients. In this review, we highlight important microbiome studies in patients with IBD and their response to different microbiome modulation therapies, and describe the differences in therapeutic response between pediatric and adult patient cohorts.

Results of the Seventh Scientific Workshop of ECCO: Precision Medicine in IBD-Prediction and Prevention of Inflammatory Bowel Disease

Inflammatory bowel disease [IBD] is a complex chronic disorder with no clear aetiology and no known cure. Despite recent advances in overall disease management and improved therapeutics, patients with IBD still experience a substantial burden. Furthermore, as the incidence continues to increase in developing areas of the world, it is expected that the burden of IBD to society will increase and exert tremendous pressure on health care systems worldwide. Therefore, new strategies to prevent the global increase of IBD are urgently required. Data are being progressively acquired on the period preceding disease diagnosis, which support the concept that IBD has a preclinical period that may reveal the triggers of disease and may be amenable to early intervention. Having a better knowledge of this preclinical period will increase the potential not only for improved understanding of disease pathogenesis and improved therapeutics, but also for disease prediction and prevention.

Fungal and Bacterial Loads: Noninvasive Inflammatory Bowel Disease Biomarkers for the Clinical Setting

Microbiome sequence data have been used to characterize Crohn's disease (CD) and ulcerative colitis (UC). Based on these data, we have previously identified microbiomarkers at the genus level to predict CD and CD relapse. However, microbial load was underexplored as a potential biomarker in inflammatory bowel disease (IBD). Here, we sought to study the use of fungal and bacterial loads as biomarkers to detect both CD and UC and CD and UC relapse. We analyzed the fecal fungal and bacterial loads of 294 stool samples obtained from 206 participants using real-time PCR amplification of the ITS2 region and the 16S rRNA gene, respectively. We combined the microbial data with demographic and standard laboratory data to diagnose ileal or ileocolonic CD and UC and predict disease relapse using the random forest algorithm. Fungal and bacterial loads were significantly different between healthy relatives of IBD patients and nonrelated healthy controls, between CD and UC patients in endoscopic remission, and between UC patients in relapse and non-UC individuals. Microbial load data combined with demographic and standard laboratory data improved the performance of the random forest models by 18%, reaching an average area under the receiver operating characteristic curve (AUC) of 0.842 (95% confidence interval [CI], 0.65 to 0.98), for IBD diagnosis and enhanced CD and UC discrimination and CD and UC relapse prediction. Our findings show that fecal fungal and bacterial loads could provide physicians with a noninvasive tool to discriminate disease subtypes or to predict disease flare in the clinical setting.

IMPORTANCE Next-generation sequence data analysis has allowed a better understanding of the pathophysiology of IBD, relating microbiome composition and functions to the disease. Microbiome composition profiling may provide efficient diagnosis and prognosis tools in IBD. However, the bacterial and fungal loads of the fecal microbiota are underexplored as potential biomarkers of IBD. Ulcerative colitis (UC) patients have higher fecal fungal and bacterial loads than patients with ileal or ileocolonic CD. CD patients who relapsed harbor more-unstable fungal and bacterial loads than those of relapsed UC patients. Fecal fungal and bacterial load data improved prediction performance by 18% for IBD diagnosis based solely on clinical data and enhanced CD and UC discrimination and prediction of CD and UC relapse. Combined with existing laboratory biomarkers such as fecal calprotectin and C-reactive protein (CRP), microbial loads may improve the diagnostic accuracy of IBD and of ileal CD and UC disease activity and prediction of UC and ileal CD clinical relapse.

Impact of Appendectomy on Gut Microbiota

Background: Considered vestigial from the classic point of view, the vermiform appendix has long been the subject of intensive studies. The recent understanding of appendix function in the context of unique architecture and bacterial complexity and density allows considering it as a safehouse for intestinal biodiversity. Methods: This review analyzes and assesses the current state of scientific knowledge regarding the role of the vermiform appendix in normal gut microbiota maintenance as a crucial factor of host homeostasis. It also highlights the difference in microbial composition between the large bowel and the appendix, as well as the association between the surgical excision, appendectomy, and dysbiosis-induced diseases. In addition, the review discusses the results of epidemiologic studies on appendectomy as a risk factor for the initiation of gastrointestinal carcinogenesis. It also highlights the association between appendectomy and a series of chronic inflammatory and neurologic disorders, including inflammatory bowel disease.

Gut Microbiota Profile in Pediatric Patients With Inflammatory Bowel Disease: A Systematic Review

Background and Aim: Accumulating evidence have implicated gut microbiota alterations in pediatric and adult patients with inflammatory bowel disease (IBD); however, the results of different studies are often inconsistent and even contradictory. It is believed that early changes in new-onset and treatment-naïve pediatric patients are more informative. We performed a systematic review to investigate the gut microbiota profiles in pediatric IBD and identify specific microbiota biomarkers associated with this disorder. Methods: Electronic databases were searched from inception to 31 July 2020 for studies that observed gut microbiota alterations in pediatric patients with IBD. Study quality was assessed using the Newcastle-Ottawa scale. Results: A total of 41 original studies investigating gut microbiota profiles in pediatric patients with IBD were included in this review. Several studies have reported a decrease in α-diversity and an overall difference in β-diversity. Although no specific gut microbiota alterations were consistently reported, a gain in Enterococcus and a significant decrease in Anaerostipes, Blautia, Coprococcus, Faecalibacterium, Roseburia, Ruminococcus, and Lachnospira were found in the majority of the included articles. Moreover, there is insufficient data to show specific microbiota bacteria associated with disease activity, location, and behavior in pediatric IBD. Conclusions: This systematic review identified evidence for differences in the abundance of some bacteria in pediatric patients with IBD when compared to patients without IBD; however, no clear overall conclusion could be drawn from the included studies due to inconsistent results and heterogeneous methodologies. Further studies with large samples that follow more rigorous and standardized methodologies are needed.

The Gut Microbial Profile of Preclinical Crohn's Disease Is Similar to That of Healthy Controls

BACKGROUND AND AIMS

It is unclear whether microbial dysbiosis plays an etiologic role in Crohn's disease (CD) or is the result of protracted inflammation. Here, we test the hypothesis that dysbiosis predates clinical CD in asymptomatic first-degree relatives (FDRs) of CD patients: normal (FDR1), with borderline inflammation (FDR2), and with frank, very early inflammation (FDR3).

METHODS

The gut microbial diversity was tested in ileocecal biopsies through next generation sequencing of the 16S rRNA gene in 10 healthy controls (HCs), 22 patients with active, untreated CD, and 25 FDRs (9 FDR1; 12 FDR2; 4 FDR3). The metagenomic functions of 41 microbiome-related processes were inferred by Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) analysis.

RESULTS

Compared with HCs, alpha diversity in CD patients was decreased, with an observed decrease in Faecalibacterium prausnitzii and increase in Bacteroides fragilis. In FDRs, microbial diversity was unchanged compared with HCs. In Operational Taxonomic Units and PICRUSt Principal coordinates and component analyses, the ellipse centroid of FDRs was diagonally opposed to that of CD patients, but close to the HC centroid. In both analyses, statistically significant differences in terms of beta diversity were found between CD and HC but not between FDR and HC.

CONCLUSIONS

In FDRs (including FDR3-who bear preclinical/biologic onset disease), we found that the microbial profile is remarkably similar to HC. If confirmed in larger studies, this finding suggests that clinical CD-associated dysbiosis could result from the changed microenvironment due to disease evolution over time.

Healthy Siblings of Children With Crohn's Disease Exhibit More Rapid Changes in Microbiota Composition as a Response to Exclusive Enteral Nutrition

BACKGROUND

The aim of this study was to determine the impact of exclusive enteral nutrition (EEN) on the microbiota composition of the newly diagnosed Crohn's disease (CD) patients and to determine the effect of EEN received for 2 days in siblings of patients with CD.

METHODS

Newly diagnosed pediatric CD patients (n = 17) and unaffected healthy siblings (n = 10) participated in the study. In CD patients, stool samples were collected at 3 time points: prior to therapy introduction, the second day of EEN therapy, and the last day of EEN therapy. In healthy siblings, stool samples were collected before the introduction of EEN and the second day of EEN. Molecular approach targeting 16S ribosomal RNA was used for analyzing the gut microbiota of participants' stool samples.

RESULTS

There was no significant difference in microbial diversity between children with CD and healthy siblings before EEN (P = .127 for HhaI digestion; P = .604 for MspI digestion) as opposed to the second day of EEN (P = .006 HhaI digestion; P = .023 MspI digestion). In healthy controls, significant changes in microbiota composition were apparent by the second day of EEN, contrary to children with CD, in whom similar changes in microbiota composition were apparent on the last day of EEN.

CONCLUSION

EEN leads to significant microbiota changes in both healthy children and children with CD. Changes in microbiota composition occur more rapidly in healthy children, whereas in children with CD, significant changes were detected at the end of EEN.

VIBRANT: automated recovery, annotation and curation of microbial viruses, and evaluation of viral community function from genomic sequences

BACKGROUND

Viruses are central to microbial community structure in all environments. The ability to generate large metagenomic assemblies of mixed microbial and viral sequences provides the opportunity to tease apart complex microbiome dynamics, but these analyses are currently limited by the tools available for analyses of viral genomes and assessing their metabolic impacts on microbiomes.

DESIGN

Here we present VIBRANT, the first method to utilize a hybrid machine learning and protein similarity approach that is not reliant on sequence features for automated recovery and annotation of viruses, determination of genome quality and completeness, and characterization of viral community function from metagenomic assemblies. VIBRANT uses neural networks of protein signatures and a newly developed v-score metric that circumvents traditional boundaries to maximize identification of lytic viral genomes and integrated proviruses, including highly diverse viruses. VIBRANT highlights viral auxiliary metabolic genes and metabolic pathways, thereby serving as a user-friendly platform for evaluating viral community function. VIBRANT was trained and validated on reference virus datasets as well as microbiome and virome data.

RESULTS

VIBRANT showed superior performance in recovering higher quality viruses and concurrently reduced the false identification of non-viral genome fragments in comparison to other virus identification programs, specifically VirSorter, VirFinder, and MARVEL. When applied to 120,834 metagenome-derived viral sequences representing several human and natural environments, VIBRANT recovered an average of 94% of the viruses, whereas VirFinder, VirSorter, and MARVEL achieved less powerful performance, averaging 48%, 87%, and 71%, respectively. Similarly, VIBRANT identified more total viral sequence and proteins when applied to real metagenomes. When compared to PHASTER, Prophage Hunter, and VirSorter for the ability to extract integrated provirus regions from host scaffolds, VIBRANT performed comparably and even identified proviruses that the other programs did not. To demonstrate applications of VIBRANT, we studied viromes associated with Crohn's disease to show that specific viral groups, namely Enterobacteriales-like viruses, as well as putative dysbiosis associated viral proteins are more abundant compared to healthy individuals, providing a possible viral link to maintenance of diseased states.

CONCLUSIONS

The ability to accurately recover viruses and explore viral impacts on microbial community metabolism will greatly advance our understanding of microbiomes, host-microbe interactions, and ecosystem dynamics. Video Abstract.

Altered Gut Microbiota Is Present in Newly Diagnosed Pediatric Patients With Inflammatory Bowel Disease

BACKGROUND AND AIMS

Clinical and experimental data suggest that gut microbiota plays an important role in the pathogenesis of inflammatory bowel disease (IBD). The aim of this study was to determine intestinal microbiota in newly diagnosed patients with IBD and to compare it with patients' healthy siblings who share same genetic and environmental background and to healthy unrelated controls.

METHODS

Molecular approach targeting 16S ribosomal RNA was employed for analyzing the gut microbiota of participants' stool samples. Terminal restriction fragment length polymorphphism analysis was performed.

RESULTS

Newly diagnosed pediatric patients with IBD (n = 19, 68.4% Crohn disease [CD], mean age 14.8 ± 0.65 years), their unaffected healthy siblings (n = 20, mean age 12.8 ± 0.85 years), and unrelated healthy controls (n = 19, mean age 10.7 ± 0.8 years) were included. Microbial diversity differed significantly between IBD patients, healthy siblings, and healthy controls (P = 0.018 for MspI digestion, P = 0.013 for HhaI digestion). No significant difference in microbial diversity was found between healthy siblings and healthy controls. In patients reduced presence of genus Eubacterium, Lactobacillus, Enterobacter and Clostridium, and increased presence of genus Streptococcus, Prevotella and Escherichia, compared with healthy siblings and healthy controls, was found.

CONCLUSION

Newly diagnosed pediatric patients with IBD show significantly less diverse microbiota and microbial composition compared with healthy siblings and healthy controls.

Differences in Gut Microbiota in Patients With vs Without Inflammatory Bowel Diseases: A Systematic Review

BACKGROUND & AIMS

Altering the intestinal microbiota has been proposed as a treatment for inflammatory bowel diseases (IBDs), but there are no established associations between specific microbes and IBD. We performed a systematic review to identify frequent associations.

METHODS

We searched the MEDLINE, EMBASE, Cochrane Database of Systematic Reviews, and Cochrane Central Register of Controlled Trials databases, through April 2, 2018 for studies that compared intestinal microbiota (from fecal or colonic or ileal tissue samples) among patients (adult or pediatric) with IBD vs healthy individuals (controls). The primary outcome was difference in specific taxa in fecal or intestinal tissue samples from patients with IBD vs controls. We used the Newcastle-Ottawa scale to assess the quality of studies included in the review.

RESULTS

We identified 2631 citations; 48 studies from 45 articles were included in the analysis. Most studies evaluated adults with Crohn's disease or ulcerative colitis. All 3 studies of Christensenellaceae and Coriobacteriaceae and 6 of 11 studies of Faecalibacterium prausnitzii reported a decreased amount of those organisms compared with controls, whereas 2 studies each of Actinomyces, Veillonella, and Escherichia coli revealed an increased amount in patients with Crohn's disease. For patients with ulcerative colitis, Eubacterium rectale and Akkermansia were decreased in all 3 studies, whereas E coli was increased in 4 of 9 studies. The microbiota diversity was either decreased or not different in patients with IBD vs controls. Fewer than 50% of the studies stated comparable sexes and ages of cases and controls.

CONCLUSIONS

In a systematic review, we found evidence for differences in abundances of some bacteria in patients with IBD vs controls, but we cannot make conclusions due to inconsistent results and methods among studies. Further large-scale studies, with better methods of assessing microbe populations, are needed.

Differences in the intestinal microbiome of healthy children and patients with newly diagnosed Crohn's disease

The aetiology of inflammatory bowel diseases (IBD) seems to be strongly connected to changes in the enteral microbiome. The dysbiosis pattern seen in Crohn’s disease (CD) differs among published studies depending on patients’ age, disease phenotype and microbiome research methods. The aims was to investigate microbiome in treatment-naive paediatric patients to get an insight into its structure at the early stage of the disease in comparison to healthy. Stool samples were obtained from controls and newly diagnosed patients prior to any intervention. Microbiota was analysed by 16SrRNAnext-generation-sequencing (NGS). Differences in the within-sample phylotype richness and evenness (alpha diversity) were detected between controls and patients. Statistically significant dissimilarities between samples were present for all used metrics. We also found a significant increase in the abundance of OTUs of the Enterococcus genus and reduction in, among others, Bifidobacterium (B. adolescentis), Roseburia (R.faecis), Faecalibacterium (F. prausnitzii), Gemmiger (G. formicilis), Ruminococcus (R. bromii) and Veillonellaceae (Dialister). Moreover, differences in alpha and beta diversities in respect to calprotectin and PCDAI were observed: patients with calprotectin <100 µg/g and with PCDAI below 10 points vs those with calprotectin >100 µg/g and mild (10–27.7 points), moderate (27.5–40 points) or severe (>40 points) CD disease activity had higher richness and diversity of gut microbiota. The results of our study highlight reduced diversity and dysbiosis at the earliest stage of the disease. Microbial imbalance and low abundance of butyrate-producing bacteria, including Bifidobacterium adolescentis, may suggest benefits of microbial modification therapy.

The microbiome of Crohn's disease aphthous ulcers

Background

Reduced intestinal microbial diversity and bacterial imbalance (dysbiosis) are seen in studies of Crohn's disease. As it is difficult to obtain biopsy samples before disease presentation, the earliest mucosal lesions in Crohn's disease, aphthous ulcers, present the best chance at assessing microbial communities at the onset of disease or a new flare. The aim of our study was to compare the microbial communities of aphthous ulcers and adjacent normal mucosa from patients with Crohn's disease with normal mucosa from controls.

Results

We did not observe bacterial imbalance or reduced alpha diversity in Crohn's disease aphthous ulcers and adjacent mucosa, relative to control biopsies. Bacteroides were common to all Crohn's disease and control samples, and there were no bacterial taxa unique to aphthous ulcers. The relative abundance of Faecalibacterium was not reduced in aphthous ulcers relative to control mucosa, and was not more likely to be detected in control samples.

Conclusions

In contrast to well-documented changes seen in late-stage Crohn's disease, microbial communities of aphthous ulcers do not display evidence of bacterial imbalance or reduced diversity. Our data suggest that dysbiosis occurs during active disease, and improves when patients are in remission.

Differences in Clinical Course, Genetics, and the Microbiome Between Familial and Sporadic Inflammatory Bowel Diseases

BACKGROUND AND AIM

Family history is the strongest risk factor for developing Crohn's disease [CD] or ulcerative colitis [UC]. We investigated whether the proximity of relationship with the affected relative and concordance for type of inflammatory bowel disease [IBD] modifies the effect of family history on phenotype and disease severity.

METHOD

This cross-sectional study included patients with a confirmed diagnosis of IBD in a clinical registry. Family history of IBD was assessed by a questionnaire ascertaining presence of disease in a first-first-degree, second-second-degree or distant relative. Our primary outcomes were disease phenotype as per the Montreal classification and severity measured by need for immunomodulator, biologic, or surgical therapy. Genotyping was performed on the Immunochip and faecal samples were subjected to 16S rRNA microbiome sequencing.

RESULTS

Our study included 2136 patients with IBD [1197 CD, 939 UC]. Just under one-third [32%] of cases ere familial IBD [17% first-degree, 21% second-degree]. Familial IBD was diagnosed at an earlier age, both in CD [26 vs 28 years, p = 0.0006] and UC [29 vs 32 years, p = 0.01]. Among CD patients, a positive family history for CD was associated with an increased risk for complicated disease in the presence of an affected family member (odds ratio [OR] 1.48, 95% confidence interval [CI] 1.07-2.03). However, this effect was significant only for first-degree relatives [OR 1.82, 95% CI 1.19-2.78].

CONCLUSIONS

A family history of CD in first-degree relatives was associated with complicated CD. Family history discordant for type of IBD or in distant relatives did not influence disease phenotype or natural history.