It is not clear how the complex interactions between diet and the intestinal microbiota affect development of mucosal inflammation or inflammatory bowel disease. We investigated interactions between ...dietary ingredients, nutrients, and the microbiota in specific pathogen-free (SPF) and germ-free (GF) mice given more than 40 unique diets; we quantified individual and synergistic effects of dietary macronutrients and the microbiota on intestinal health and development of colitis.
C56BL/6J SPF and GF mice were placed on custom diets containing different concentrations and sources of protein, fat, digestible carbohydrates, and indigestible carbohydrates (fiber). After 1 week, SPF and GF mice were given dextran sulfate sodium (DSS) to induce colitis. Disease severity was determined based on the percent weight change from baseline, and modeled as a function of the concentration of each macronutrient in the diet. In unchallenged mice, we measured intestinal permeability by feeding mice labeled dextran and measuring levels in blood. Feces were collected and microbiota were analyzed by 16S rDNA sequencing. We collected colons from mice and performed transcriptome analyses.
Fecal microbiota varied with diet; the concentration of protein and fiber had the strongest effect on colitis development. Among 9 fiber sources tested, psyllium, pectin, and cellulose fiber reduced the severity of colitis in SPF mice, whereas methylcellulose increased severity. Increasing dietary protein increased the density of the fecal microbiota and the severity of colitis in SPF mice, but not in GF mice or mice given antibiotics. Psyllium fiber reduced the severity of colitis through microbiota-dependent and microbiota-independent mechanisms. Combinatorial perturbations to dietary casein protein and psyllium fiber in parallel accounted for most variation in gut microbial density and intestinal permeability in unchallenged mice, as well as the severity of DSS-induced colitis; changes in 1 ingredient could be offset by changes in another.
In an analysis of the effects of different dietary components and the gut microbiota on mice with and without DSS-induced colitis, we found complex mixtures of nutrients affect intestinal permeability, gut microbial density, and development of intestinal inflammation.
Non-alcoholic steatohepatitis (NASH) is a severe form of non-alcoholic fatty liver disease (NAFLD) that is responsible for a growing fraction of cirrhosis and liver cancer cases worldwide. Changes in ...the gut microbiome have been implicated in NASH pathogenesis, but the lack of suitable murine models has been a barrier to progress. We have therefore characterized the microbiome in a well-validated murine NASH model to establish its value in modeling human disease.
The composition of intestinal microbiota was monitored in mice on a 12- or 24-week NASH protocol consisting of high fat, high sugar Western Diet (WD) plus once weekly i.p injection of low-dose CCl4. Additional mice were subjected to WD-only or CCl4-only conditions to assess the independent effect of these variables on the microbiome.
There was substantial remodeling of the intestinal microbiome in NASH mice, characterized by declines in both species diversity and bacterial abundance. Based on changes to beta diversity, microbiota from NASH mice clustered separately from controls in principal coordinate analyses. A comparison between WD-only and CCl4-only controls with the NASH model identified WD as the primary driver of early changes to the microbiome, resulting in loss of diversity within the 1st week. A NASH signature emerged progressively at weeks 6 and 12, including, most notably, a reproducible bloom of the Firmicute order Erysipelotrichales.
We have established a valuable model to study the role of gut microbes in NASH, enabling us to identify a new NASH gut microbiome signature.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
The gut microbiota codevelops with the immune system beginning at birth. Mining the microbiota for bacterial strains responsible for shaping the structure and dynamic operations of the innate and ...adaptive arms of the immune system represents a formidable combinatorial problem but one that needs to be overcome to advance mechanistic understanding of microbial community and immune system coregulation and to develop new diagnostic and therapeutic approaches that promote health. Here, we discuss a scalable, less biased approach for identifying effector strains in complex microbial communities that impact immune function. The approach begins by identifying uncultured human fecal microbiota samples that transmit immune phenotypes to germ-free mice. Clonally arrayed sequenced collections of bacterial strains are constructed from representative donor microbiota. If the collection transmits phenotypes, effector strains are identified by testing randomly generated subsets with overlapping membership in individually housed germ-free animals. Detailed mechanistic studies of effector strain-host interactions can then be performed.
Determining which combinations of human gut bacterial strains shape immune function presents a huge challenge. Ahern et al. propose an approach that should facilitate discovery of microbe-based therapeutics, which involves culturing a person’s gut community and efficiently mining it for strains that transmit immunomodulatory activities to germ-free mice.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Functional characterization of the microbiome’s influence on host physiology has been dominated by a few characteristic example strains that have been studied in detail. However, the extensive ...development of methods for high-throughput bacterial isolation and culture over the past decade is enabling functional characterization of the broader microbiota that may impact human health. Characterizing the understudied majority of human microbes and expanding our functional understanding of the diversity of the gut microbiota could enable new insights into diseases with unknown etiology, provide disease-predictive microbiome signatures, and advance microbial therapeutics. We summarize high-throughput culture-dependent platforms for characterizing bacterial strain function and host-interactions. We elaborate on the importance of these technologies in facilitating mechanistic studies of previously unexplored microbes, highlight new opportunities for large-scale in vitro screens of host-relevant microbial functions, and discuss the potential translational applications for microbiome science.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
IMPORTANCE: The effect of rationally defined nonpathogenic, nontoxigenic, commensal strains of Clostridia on prevention of Clostridioides difficile infection (CDI) is unknown. OBJECTIVE: To determine ...the efficacy of VE303, a defined bacterial consortium of 8 strains of commensal Clostridia, in adults at high risk for CDI recurrence. The primary objective was to determine the recommended VE303 dosing for a phase 3 trial. DESIGN, SETTING, AND PARTICIPANTS: Phase 2, randomized, double-blind, placebo-controlled, dose-ranging study conducted from February 2019 to September 2021 at 27 sites in the US and Canada. The study included 79 participants aged 18 years or older who were diagnosed with laboratory-confirmed CDI with 1 or more prior CDI episodes in the last 6 months and those with primary CDI at high risk for recurrence (defined as aged ≥75 years or ≥65 years with ≥1 risk factors: creatinine clearance <60 mL/min/1.73 m2, proton pump inhibitor use, remote >6 months earlier CDI history). INTERVENTIONS: Participants were randomly assigned to high-dose VE303 (8.0 × 109 colony-forming units CFUs) (n = 30), low-dose VE303 (1.6 × 109 CFUs) (n = 27), or placebo capsules (n = 22) orally once daily for 14 days. MAIN OUTCOMES AND MEASURES: The primary efficacy end point was the proportion of participants with CDI recurrence at 8 weeks using a combined clinical and laboratory definition. The primary efficacy end point was analyzed in 3 prespecified analyses, using successively broader definitions for an on-study CDI recurrence: (1) diarrhea consistent with CDI plus a toxin-positive stool sample; (2) diarrhea consistent with CDI plus a toxin-positive, polymerase chain reaction–positive, or toxigenic culture–positive stool sample; and (3) diarrhea consistent with CDI plus laboratory confirmation or (in the absence of a stool sample) treatment with a CDI-targeted antibiotic. RESULTS: Baseline characteristics were similar across the high-dose VE303 (n = 29; 1 additional participant excluded from efficacy analysis), low-dose VE303 (n = 27), and placebo (n = 22) groups. The participants’ median age was 63.5 years (range, 24-96); 70.5% were female; and 1.3% were Asian, 1.3% Black, 2.6% Hispanic, and 96.2% White. CDI recurrence rates through week 8 (using the efficacy analysis 3 definition) were 13.8% (4/29) for high-dose VE303, 37.0% (10/27) for low-dose VE303, and 45.5% (10/22) for placebo (P = .006, high-dose VE303 vs placebo). CONCLUSIONS AND RELEVANCE: Among adults with laboratory-confirmed CDI with 1 or more prior CDI episodes in the last 6 months and those with primary CDI at high risk for recurrence, high-dose VE303 prevented recurrent CDI compared with placebo. A larger, phase 3 study is needed to confirm these findings. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT03788434
A low-error 16S ribosomal RNA amplicon sequencing method, in combination with whole-genome sequencing of >500 cultured isolates, was used to characterize bacterial strain composition in the fecal ...microbiota of 37 U.S. adults sampled for up to 5 years. Microbiota stability followed a power-law function, which when extrapolated suggests that most strains in an individual are residents for decades. Shared strains were recovered from family members but not from unrelated individuals. Sampling of individuals who consumed a monotonous liquid diet for up to 32 weeks indicated that changes in strain composition were better predicted by changes in weight than by differences in sampling interval. This combination of stability and responsiveness to physiologic change confirms the potential of the gut microbiota as a diagnostic tool and therapeutic target.
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BFBNIB, NMLJ, NUK, PNG, SAZU, UL, UM, UPUK
Identifying a scalable, unbiased method for discovering which members of the human gut microbiota influence specific physiologic, metabolic, and immunologic phenotypes remains a challenge. We ...describe a method in which a clonally arrayed collection of cultured, sequenced bacteria was generated from one of several human fecal microbiota samples found to transmit a particular phenotype to recipient germ-free mice. Ninety-four bacterial consortia of diverse size, randomly drawn from the culture collection, were introduced into germ-free animals. We identified an unanticipated range of bacterial strains that promoted accumulation of colonic regulatory T cells (T(regs)) and expansion of Nrp1(lo/-) peripheral T(regs), as well as strains that modulated mouse adiposity and cecal metabolite concentrations, using feature selection algorithms and follow-up monocolonizations. This combinatorial approach enables a systems-level understanding of microbial contributions to human biology.
The interrelationships between our diets and the structure and operations of our gut microbial communities are poorly understood. A model community of 10 sequenced human gut bacteria was introduced ...into gnotobiotic mice, and changes in species abundance and microbial gene expression were measured in response to randomized perturbations of four defined ingredients in the host diet. From the responses, we developed a statistical model that predicted over 60% of the variation in species abundance evoked by diet perturbations, and we were able to identify which factors in the diet best explained changes seen for each community member. The approach is generally applicable, as shown by a follow-up study involving diets containing various mixtures of pureed human baby foods.
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Diet and nutritional status are among the most important modifiable determinants of human health. The nutritional value of food is influenced in part by a person's gut microbial community ...(microbiota) and its component genes (microbiome). Unraveling the interrelations among diet, the structure and operations of the gut microbiota, and nutrient and energy harvest is confounded by variations in human environmental exposures, microbial ecology, and genotype. To help overcome these problems, we created a well-defined, representative animal model of the human gut ecosystem by transplanting fresh or frozen adult human fecal microbial communities into germ-free C57BL/6J mice. Culture-independent metagenomic analysis of the temporal, spatial, and intergenerational patterns of bacterial colonization showed that these humanized mice were stably and heritably colonized and reproduced much of the bacterial diversity of the donor's microbiota. Switching from a low-fat, plant polysaccharide-rich diet to a high-fat, high-sugar "Western" diet shifted the structure of the microbiota within a single day, changed the representation of metabolic pathways in the microbiome, and altered microbiome gene expression. Reciprocal transplants involving various combinations of donor and recipient diets revealed that colonization history influences the initial structure of the microbial community but that these effects can be rapidly altered by diet. Humanized mice fed the Western diet have increased adiposity; this trait is transmissible via microbiota transplantation. Humanized gnotobiotic mice will be useful for conducting proof-of-principle "clinical trials" that test the effects of environmental and genetic factors on the gut microbiota and host physiology. Nearly full-length 16S rRNA gene sequences are deposited in GenBank under the accession numbers GQ491120 to GQ493997.
The role of specific gut microbes in shaping body composition remains unclear. We transplanted fecal microbiota from adult female twin pairs discordant for obesity into germ-free mice fed low-fat ...mouse chow, as well as diets representing different levels of saturated fat and fruit and vegetable consumption typical of the U.S. diet. Increased total body and fat mass, as well as obesity-associated metabolic phenotypes, were transmissible with uncultured fecal communities and with their corresponding fecal bacterial culture collections. Cohousing mice harboring an obese twin's microbiota (Ob) with mice containing the lean co-twin's microbiota (Ln) prevented the development of increased body mass and obesity-associated metabolic phenotypes in Ob cage mates. Rescue correlated with invasion of specific members of Bacteroidetes from the Ln microbiota into Ob microbiota and was diet-dependent. These findings reveal transmissible, rapid, and modifiable effects of diet-by-microbiota interactions.
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