Environmental and intrinsic factors shaping gut microbiota composition and diversity and its relation to metabolic health in children and early adolescents: A population-based study

ABSTRACT

Background

Gut microbiota, by influencing multiple metabolic processes in the host, is an important determinant of human health and disease. However, gut dysbiosis associated with metabolic complications shows inconsistent patterns. This is likely driven by factors shaping gut microbial composition that have largely been under-evaluated, at a population level, in school-age children, especially from developing countries.     

Human resident gut microbe Bacteroides thetaiotaomicron regulates colonic neuronal innervation and neurogenic function

ABSTRACT

Background and aims

As the importance of gut–brain interactions increases, understanding how specific gut microbes interact with the enteric nervous system (ENS), which is the first point of neuronal exposure becomes critical. Our aim was to understand how the dominant human gut bacterium Bacteroides thetaiotaomicron (Bt) regulates anatomical and functional characteristics of the ENS.     

Additional Candida albicans administration enhances the severity of dextran sulfate solution induced colitis mouse model through leaky gut-enhanced systemic inflammation and gut-dysbiosis but attenuated by Lactobacillus rhamnosus L34

ABSTRACT

Candida albicans

is abundant in the human gut mycobiota but this species does not colonize the mouse gastrointestinal tract. C. albicans administration in dextran-sulfate solution (DSS) induced-colitis mouse model (DSS+Candida) might resemble more to human condition, therefore, a DSS colitis model with Candida administration was studied; first, to test the influence of fungi in DSS model and second, to test the efficacy of Lactobacillus rhamnosus L34. We demonstrated serum (1→3)-β-D-glucan (BG) elevation in patients with IBD and endoscopic moderate colitis in clinical remission, supporting the possible influence of gut fungi toward IBD in human. Then, in mouse model, Candida gavage was found to worsen the DSS model indicated by higher mortality rate, more severe colon histology and enhanced gut-leakage (FITC-dextran assay, endotoxemia, serum BG and blood bacterial burdens) but did not affect weight loss and diarrhea. DSS+Candida induced higher pro-inflammatory cytokines both in blood and in intestinal tissue. Worsened systemic pro-inflammatory cytokine responses in DSS+Candida compared with DSS alone was possibly due to the more severe translocation of LPS, BG and bacteria (not fungemia) from gut into systemic circulation. Interestingly, bacteremia from Pseudomonas aeruginosa was more frequently isolated from DSS+Candida than DSS alone. In parallel, P. aeruginosa was also isolated from fecal culture in most of the mice in DSS+Candida group supported by prominent Gammaproteobacteria in fecal microbioata analysis. However, L. rhamnosus L34 attenuated both DSS+Candida and DSS model through the attenuation of gut local inflammation (cytokines and histology), gut-leakage severity, fecal dysbiosis (culture method and microbiome analysis) and systemic inflammation (serum cytokines). In conclusion, gut Candida in DSS model induced fecal bacterial dysbiosis and enhanced leaky-gut induced bacteremia. Probiotic treatment strategy aiming to reduce gut-fungi and fecal dysbiosis could attenuate disease severity. Investigation on gut fungi in patients with IBD is highly interesting.     

Faecal microbiota signatures of IBD and their relation to diagnosis,disease phenotype,inflammation, treatment escalation and anti-TNF response in a European Multicentre Study (IBD-Character)

Abstract

Method

We examined faecal samples, using the GA-map? Dysbiosis Test, to associate gut microbiota composition with Crohn’s disease (CD) and ulcerative colitis (UC) and to identify markers for future biomarker identification. We conducted a prospective case-control study (EU-ref. no. 305676) in an inception cohort of 324 individuals (64?CD, 84 UC, 116 symptomatic non-IBD controls and 44 healthy controls) across five European centres and examined 54 predetermined bacterial markers. We categorized patients according to the Montreal Classification and calculated the dysbiosis index (DI). Non-parametric tests were used to compare groups and the Bonferroni correction to adjust for multiple comparisons.     

The composition and richness of the gut microbiota differentiate the top Polish endurance athletes from sedentary controls

ABSTRACT

Background

Little data are available on the subject of gut microbiota composition in endurance athletes as well as connections between diet and specific bacteria abundance. However, most studies suggest that athletes’ microbiota undergoes major alterations, which may contribute to increased physical performance. Therefore, we decided to investigate differences in gut microbiota between healthy controls and endurance athletes.     

CODY enables quantitatively spatiotemporal predictions on in vivo gut microbial variability induced by diet intervention

Microbial variations in the human gut are harbored in temporal and spatial heterogeneity, and quantitative prediction of spatiotemporal dynamic changes in the gut microbiota is imperative for development of tailored microbiome-directed therapeutics treatments, e.g. precision nutrition. Given the high-degree complexity of microbial variations, subject to the dynamic interactions among host, microbial, and environmental factors, identifying how microbiota colonize in the gut represents an important challenge. Here we present COmputing the DYnamics of microbiota (CODY), a multiscale framework that integrates species-level modeling of microbial dynamics and ecosystem-level interactions into a mathematical model that characterizes spatial-specific in vivo microbial residence in the colon as impacted by host physiology. The framework quantifies spatiotemporal resolution of microbial variations on species-level abundance profiles across site-specific colon regions and in feces, independent of a priori knowledge. We demonstrated the effectiveness of CODY using cross-sectional data from two longitudinal metagenomics studies—the microbiota development during early infancy and during short-term diet intervention of obese adults. For each cohort, CODY correctly predicts the microbial variations in response to diet intervention, as validated by available metagenomics and metabolomics data. Model simulations provide insight into the biogeographical heterogeneity among lumen, mucus, and feces, which provides insight into how host physical forces and spatial structure are shaping microbial structure and functionality.

Changes in the human gut microbiome composition are connected with development of numerous diseases, like obesity, type-2 diabetes, and immune dysfunction (1–3). Quantitative understanding and predicting how microbial variations are determined are crucial for designing microbiome-directed therapies that target chronic metabolic diseases (4, 5). However, this remains challenging due to the temporal and spatial heterogeneity along the human gut resulting from a dynamic interplay among host, microbial, and environmental conditions (6, 7). Diet is recognized as a controllable and pivotal environmental factor in shaping longitudinal microbial landscape development (8, 9), such as early childhood colonization (10) and long-term adulthood stabilization (11). While profiling of fecal samples enables a snapshot of consequential changes of the fecal microbiota in response to different stimuli, e.g. dietary changes (12–14), it is still far from describing the intrinsic dynamics of how microbiome colonize in the gut. Recently, the spatial heterogeneity of microbial composition between lumen and mucus has been recognized in mice (15, 16), but similar studies in humans is impossible with current techniques. In addition, measurements of absolute abundance profiles are required to correct the artifacts associated with relative abundance that confound revealing the interplay between microbial variations and health (17). Therefore, methods that enable quantifying the absolute, temporal, and spatial variations of in vivo human gut microbiota are needed to understand how to maintain or restore healthy microbiota.Computational models are widely used to decipher microbial complexity and response to perturbations (18). Most existing models have limited usage as they only address specific elements of the multidimensional interaction mechanisms. For example, similarity-based (19) and rule-mining models (20) describe microbial–microbial interactions without considering temporal dependency. The dynamic Bayesian model enables incorporation of directed interactions and longitudinal dataset (21), while reliance on training dataset and difficulties in model selection render these stochastic models confining to specific statistic condition and predictions are therefore not consistent and generalizable (22). The generalized Lotka–Volterra model (18, 23, 24) represents a step forward to simulate dynamics via formulating microbial growth rate as a lumped term, but adherence to assumptions of pairwise interactions-driven community dynamics and constant environment limits their predictive power. Genome-scale models (GEMs) (25) provide a valuable resource for studying structured microbial metabolism. With GEMs, microbial metabolic capacity, microbe–microbe interactions (26–28), microbial–diet interactions (12), and structural changes of two-species cocultures (29) are characterized using flux balance analysis (FBA). With rare exceptions, FBA requires a priori knowledge of metabolite uptake fluxes distributed among community members, with current limitations on these resources, faces challenges with modeling multispecies communities in a dynamic manner (30). Therefore, in adapting a computational framework that can simulate microbiome dynamics along the human gut, one encounters three challenges: 1) endogenously, the intrinsic dynamics not only emerge from the large number of microbiota components but also through the intricate and dynamic ways they interact (31, 32); 2) exogenously, the microbiota is exposed to a series of host–microbe metabolic axes (33), such as colonic physical forces (34), nascent colonization, and nutrient conditions; and 3) spatial structure of the in vivo microbiota localization plays a significant role impacting 1 and 2 (24).Here, we bridge the current theoretical gap by developing a multiscale framework for COmputing the DYnamics of gut microbiota (CODY), which enables identification and quantification of spatiotemporal-specific variations of gut microbiome absolute and relative abundance profiles, without a prior knowledge of microbiome interactions. We evaluated CODY’s performance by comparing model simulations with longitudinal changes in the microbial composition in fecal samples and in plasma metabolomics of two cohorts: 1) long-term development of the gut microbiome in early infancy and 2) short-term variation patterns of the gut microbiome in obese adults experiencing diet intervention. Comparison of model simulations with experimental data demonstrated predictive strength of the CODY modeling framework and hence lays the foundation for performing design of microbiome-directed therapeutics or of precision nutrition based on CODY simulations. The source code of CODY is freely available together with full documentation at https://github.com/JunGeng-Sysbio-Chalmers/CODY1.0_SourceCode.     

Continuous pre- and post-transplant exposure to a disease-associated gut microbiome promotes hyper-acute graft-versus-host disease in wild-type mice

ABSTRACT

Objective

The gut microbiome plays a key role in the development of acute graft-versus-host disease (GVHD) following allogeneic hematopoietic stem cell transplantation. Here we investigate the individual contribution of the pre- and post-transplant gut microbiome to acute GVHD using a well-studied mouse model.     

Gut microbiota regulate tumor metastasis via circRNA/miRNA networks

ABSTRACT

Background

Increasing evidence indicates that gut microbiota plays an important role in cancer progression. However, the underlying mechanism remains largely unknown. Here, we report that broad-spectrum antibiotics (ABX) treatment leads to enhanced metastasis by the alteration of gut microbiome composition.     

Altered gut microbiome composition in patients with Vogt-Koyanagi-Harada disease

ABSTRACT

Background

Vogt-Koyanagi-Harada (VKH) disease is a multisystemic autoimmune disorder characterized by granulomatous panuveitis. Gut microbiome has been considered to play a role in the pathogenesis of this disease but whether the alternation of gut microbiome was involved is unclear. This study was set up to identify abnormalities of gut microbiome composition in VKH disease.     

Long-term effects of antimicrobial drugs on the composition of the human gut microbiota

ABSTRACT

Introduction

Antimicrobial drugs are known to have effects on the human gut microbiota. We studied the long-term temporal relationship between several antimicrobial drug groups and the composition of the human gut microbiota determined in feces samples.     

Gut commensal derived-valeric acid protects against radiation injuries

ABSTRACT

Background

Hematopoietic and intestinal systems side effects are frequently found in patients who suffered from accidental or medical radiation exposure. In this case, we investigated the effects of gut microbiota produced-valeric acid (VA) on radiation-induced injuries.     

Gut microecological regulation on bronchiolitis and asthma in children: A review

Introduction

Asthma and bronchiolitis in children are considered common clinical problems associated with gut microbiota. However, the exact relationship between gut microbiota and the above-mentioned diseases remains unclear. Here, we discussed recent advances in understanding the potential mechanism underlying immune regulation of gut microbiota on asthma and bronchiolitis in children as well as the role of the gut–lung axis.

Methods

We retrieved and assessed all relevant original articles related to gut microbiota, airway inflammation-induced wheezing in children, and gut–lung axis studies from databases that have been published so far, including PubMed/MEDLINE, Scopus, Google Scholar, China National Knowledge Infrastructure (CNKI) and the Wanfang Database.

Results

The infant period is critical for the development of gut microbiota, which can be influenced by gestational age, delivery mode, antibiotic exposure and feeding mode. The gut microbiota in children with asthma and bronchiolitis is significantly distinct from those in healthy subjects. Gut microbiota dysbiosis is implicated in asthma and bronchiolitis in children. The presence of intestinal disturbances in lung diseases highlights the importance of the gut–lung axis.

Conclusion

Gut microbiota dysbiosis potentially increases the risk of asthma and bronchiolitis in children. Moreover, a deeper understanding of the gut–lung axis with regard to the gut microbiota of children with respiratory diseases could contribute to clinical practice for pulmonary diseases.     

Changes in the fecal bacterial microbiota associated with disease severity in alcoholic hepatitis patients

ABSTRACT

Background and Aims

Alcoholic hepatitis is the most severe form of alcohol-related liver disease. While the gut microbiome is known to play a role in disease development and progression, less is known about specific compositional changes of the gut bacterial microbiome associated with disease severity. Therefore, the aim of our study was to correlate gut microbiota features with disease severity in alcoholic hepatitis patients.     

The protective effect of Bifidobacterium bifidum G9-1 against mucus degradation by Akkermansia muciniphila following small intestine injury caused by a proton pump inhibitor and aspirin

ABSTRACT

Background

Proton pump inhibitors (PPIs) can alleviate upper gastrointestinal injury but paradoxically exacerbate aspirin (ASA)-induced small intestine injury. In this study, our goal was to simulate this exacerbation by developing an appropriate animal model, which may help in establishing treatments. Methods: Male mice were fed a 60% fructose diet for 9 weeks, then administered 200 mg/kg ASA 3 h before sacrifice. The PPI omeprazole was administered intraperitoneally once daily for 9 weeks. Bifidobacterium bifidum G9-1 was administered orally for the last week. In addition, Akkermansia muciniphila was administered orally for 9 weeks instead of omeprazole. Results: ASA-induced small-intestine injury was observed in high-fructose fed mice. Omeprazole exacerbated ASA-induced intestinal damage, significantly decreased Bifidobacteria levels, and significantly increased A. muciniphila counts in the jejunum. The direct administration of A. muciniphila caused thinning of the jejunum mucus layer, which was also observed in mice that received ASA and omeprazole. On the other hand, the administration of Bifidobacterium bifidum G9-1 inhibited A. muciniphila growth and reduced thinning of the mucus layer. The number of goblet cells in the jejunum was reduced by the administration of ASA and omeprazole, while Bifidobacterium bifidum G9-1 prevented the reduction. Conclusions: These results suggest that omeprazole-induced gut dysbiosis promotes Akkermansia growth and inhibits Bifidobacterium growth, leading to a thinning of the mucus layer through a reduction in goblet cells in the small intestine. Probiotics are, therefore, a promising approach for the treatment of small intestine injury.     

Gut microbiome contributions to altered metabolism in a pig model of undernutrition

The concept that gut microbiome-expressed functions regulate ponderal growth has important implications for infant and child health, as well as animal health. Using an intergenerational pig model of diet restriction (DR) that produces reduced weight gain, we developed a feature-selection algorithm to identify representative characteristics distinguishing DR fecal microbiomes from those of full-fed (FF) pigs as both groups consumed a common sequence of diets during their growth cycle. Gnotobiotic mice were then colonized with DR and FF microbiomes and subjected to controlled feeding with a pig diet. DR microbiomes have reduced representation of genes that degrade dominant components of late growth-phase diets, exhibit reduced production of butyrate, a key host-accessible energy source, and are causally linked to reduced hepatic fatty acid metabolism (β-oxidation) and the selection of alternative energy substrates. The approach described could aid in the development of guidelines for microbiome stewardship in diverse species, including farm animals, in order to support their healthy growth.

Undernutrition afflicts over 200 million children worldwide and accounts for 45% of mortality in children under 5 y (1). Children with acute malnutrition exhibit wasting (impaired ponderal growth), often accompanied by stunting (reduced linear growth), deficits in bone development, neurodevelopment, and immunity, as well as perturbed metabolism (2, 3). Epidemiologic studies indicate that acute malnutrition in children is not due to food insecurity alone and that perturbed gut microbial community development is a contributing factor; children with severe acute malnutrition (SAM) and moderate acute malnutrition (MAM; weight-for-length z-scores are, respectively, 2 to 3 and >3 SDs below World Health Organization mean values) have microbiota that appear “younger” (more immature) compared to those of chronologically aged-matched healthy children (4–6). Studies in gnotobiotic mice colonized with microbiota from healthy and undernourished children have provided evidence that immature microbiota can transmit features of undernutrition (5, 7). These tests of causality inspired development of microbiota-directed complementary foods (MDCFs) designed to repair the microbiota of undernourished children. A controlled feeding study, involving a small group of 12- to 18-mo-old Bangladeshi children with MAM, identified an MDCF formulation that repaired their microbiota; repair was associated with a marked change in their plasma proteome characterized by alterations in levels of key mediators of bone growth, metabolism, immune function, and neurodevelopment toward a healthy state (5). A larger, longer randomized controlled study showed that this MDCF produced a superior effect on ponderal growth compared to a ready-to-use supplementary food even though the caloric density of the MDCF was 20% lower (8).These observations prompted us to examine the influence of the gut microbiome on weight gain in the domestic pig, Sus scrofa domesticus. We focused on this species for several reasons. First, pigs account for ∼35% of global meat intake, second only to poultry (9, 10). Production costs are heavily influenced by how efficiently feed is transformed into body mass, as well as the degree of growth uniformity across animals (11). Second, pigs have been used as a model for studying human nutrition and metabolism because of the many ways in which they are anatomically, physiologically, and metabolically similar to humans (12, 13). Third, most of the commercial pig industry raises animals in highly controlled farming systems engineered to promote efficient and consistent growth phenotypes. These systems typically include phased feeding programs that transition animals from early, more costly, readily digestible, nutrient-rich diets to later, less-expensive diets with less nutrient fortification where energy/nutrient extraction is more dependent on expressed metabolic activities encoded in the gut microbiome. A central premise of the current study is that in order to more fully realize the goal of predictable robust weight gain at affordable prices, additional knowledge is needed regarding codevelopment of the gut microbiome and host; this knowledge could allow diets to be formulated based on greater understanding of which components (features) of the community play key roles in transforming dietary components to products that the animals use to satisfy their growth requirements (14). The environmentally controlled settings for raising pigs provide great opportunities for performing longitudinal studies designed to delineate these interactions between diet, microbiome features, and host physiology. Finally, the need to focus on whether/how the gut microbiome contributes to growth is made more pressing by international mandates to eliminate use of subtherapeutic antibiotics for growth promotion of farm animals because of the spread of antibiotic-resistant organisms (15, 16).In the present study, we developed an algorithm (entropy-based method for microbial ecology research, EMMER), based on the von Neumann entropy calculation from quantum information theory (17, 18), to identify representative characteristics of fecal microbiomes serially sampled from litters of pigs that were or were not subjected to maternal diet restriction (DR) in utero and then provided either ad libitum access to, or restricted amounts of, a sequence of diets commonly given to farm-reared pigs as they complete their growth cycle. A 45% lower weight was attained by DR compared to full-fed (FF) pigs by the third postnatal month and this difference was sustained for the remainder of the 5-mo-long study. DR microbiomes exhibited a significantly reduced representation of genes encoding enzymes involved in the degradation of polysaccharides from dominant components of diets administered after postnatal day 70. These differences in the DR microbiome were associated with diminished fecal levels of butyrate, a major source of host energy, and significant increases in plasma levels of triglycerides, glucogenic amino acids, and urea cycle precursors. Functional features of DR and FF fecal microbiomes, collected during the period of consumption of the corn/soy-rich “finisher” diet (the last given during the feeding program), were subsequently assayed in gnotobiotic mice under controlled feeding conditions where all animals were provided the same amount of the finisher phase pig diet. The results confirmed the reduced capacity of the DR microbiome to generate butyrate. Moreover, mice colonized with the DR microbiome also exhibited reduced fatty acid oxidation in the liver, a metabolic effect that could explain the redirection of amino acids from protein synthesis to replenish hepatic energy reserves in DR pigs. Marrying longitudinal studies of farm animal gut microbiome development and function, conducted in well-engineered farming systems, with gnotobiotic mouse models that incorporate the microbial communities and diets of the farm animals, provides an opportunity to develop an informed set of practices for microbiome husbandry that promotes healthy growth. The results could have substantial economic and societal impact during this time of increasing global food insecurity and when producing sufficient amounts of high-quality protein to feed a rapidly expanding human population is a major challenge (9).     

Intestinal permeability,microbial translocation,changes in duodenal and fecal microbiota,and their associations with alcoholic liver disease progression in humans

ABSTRACT

Background

Animal data suggest a role of the gut-liver axis in progression of alcoholic liver disease (ALD), but human data are scarce especially for early disease stages.     

Thumb sucking or nail biting in childhood and adolescence is associated with an increased risk of Crohn’s disease: results from a large case–control study

Abstract

Background

The hygiene hypothesis suggests that a reduction in microbial exposure contributes to an impaired immune response later in life and increases the incidence of immune-mediated diseases such as inflammatory bowel diseases (IBD). Thumb sucking and nail biting are two early habits that modulate the oral microbiota composition and antigen load.     

Campylobacter concisus is prevalent in the gastrointestinal tract of patients with microscopic colitis

Abstract

Objectives

Microscopic colitis (MC) is potentially induced by an inflammatory reaction to a luminal gut factor. The emerging pathogen Campylobacter concisus is associated with prolonged diarrhoea and subsequently increased risk of MC. We aimed to examine the prevalence of C. concisus in clinical samples from MC patients, analyse the subtypes collagenous colitis (CC) and lymphocytic colitis (LC), and characterise C. concisus isolates from MC patients by genomic sequencing.     

Altered Gut Microbiota in Type 2 Diabetes: Just a Coincidence?

Purpose of Review

In the last decade many studies have suggested an association between the altered gut microbiota and multiple systemic diseases including diabetes. In this review, we will discuss potential pathophysiological mechanisms, the latest findings regarding the mechanisms linking gut dysbiosis and type 2 diabetes (T2D), and the results obtained with experimental modulation of microbiota.

Recent Findings

In T2D, gut dysbiosis contributes to onset and maintenance of insulin resistance. Different strategies that reduce dysbiosis can improve glycemic control.

Summary

Evidence in animals and humans reveals differences between the gut microbial composition in healthy individuals and those with T2D. Changes in the intestinal ecosystem could cause inflammation, alter intestinal permeability, and modulate metabolism of bile acids, short-chain fatty acids and metabolites that act synergistically on metabolic regulation systems contributing to insulin resistance. Interventions that restore equilibrium in the gut appear to have beneficial effects and improve glycemic control. Future research should examine in detail and in larger studies other possible pathophysiological mechanisms to identify specific pathways modulated by microbiota modulation and identify new potential therapeutic targets.