Gut microbiota and health

This study investigates sex-specific effects of gut microbiome on bile acid metabolism by transplanting feces from male and female mice and measuring bile acid profiles and gene expression.

This study uses metagenomic analysis to characterize the fecal microbiota of Eastern Bongos, identifying dominant phyla, functional classifications, and potential pathogenic microorganisms.

The paper evaluates the potential and challenges of building an IBS classifier using integrated microbiome data, finding that while XGBoost achieves moderate accuracy, performance drops significantly when tested across diverse datasets.

This study identifies genetic factors enabling Bacteroides fragilis to transition from commensal to pathogenic by analyzing 813 strains and their genomic diversity.

The paper investigates how gut microbiota from male and female maternal immune activation (MIA) mice affects ASD-like behaviors in recipient mice, revealing sex-specific differences in gut reactivity and neuroinflammation.

This paper introduces CompDA, a new method for health-microbiome association analysis that accounts for compositional data and ecological interactions, and demonstrates its effectiveness through simulations and real-data applications.

The paper shows that a bacterial operon in the gut microbiome can reduce drug toxicity during cancer treatment by inactivating 5-fluorouracil.

This study identifies a brain-gut circuit involving Brunner's glands that regulates intestinal microbiome composition and immunity.

This study shows that antibiotic treatment reduces neuroinflammation and neurodegeneration after TBI in mice by altering the gut microbiome.

This study uses an in vitro model to show that inulin is poorly fermented by the gut microbiota of children with severe acute malnutrition, while legume-based feeds and milk oligosaccharides are more effectively fermented.

This study builds machine learning models to predict human tissue of origin from microbiome data and shows contaminants can contribute to model performance.

The paper introduces interaction models for microbial data to predict community functions and resistance genes, showing improved performance in diverse datasets.

The paper shows how species in gut bacterial communities can survive or go extinct based on resource availability and metabolic interactions, identifying emergent survival and community-driven extinctions.

The paper develops improved mouse models of the small intestine microbiota using region-specific human intestinal sampling and in vitro culturing, showing increased diversity and reproducibility in colonization.

This study shows that long-term fasting changes gut microbial composition and function, as well as the serum metabolome, with significant shifts in microbial species and metabolite levels.

S-Wipe is a low-cost stool collection method for metabolomic gut health tracking that enables reproducible, stable, and convenient sample collection for diagnostic and longitudinal studies.

The paper identifies microbiota, bile acid, and inflammation marker associations in Crohn's disease and Ulcerative Colitis using integrated omics data from 1,257 individuals.

The paper develops microbiome-based biomarkers to identify suitable patients for microbiome-based therapies in Parkinson's disease, showing that not all patients have dysbiotic microbiomes and that dysbiotic microbiomes vary in features.

This study investigates how baseline gut microbiome composition affects resilience to and recovery from antibiotic treatment, identifying key taxa and functional modules associated with resilience.

This study shows Cyclocarya paliurus polysaccharides reduce obesity and lipid dysmetabolism in high fat diet-fed mice by modulating gut microbiota.

This study reveals interindividual variability in gut microbial metabolism of immunosuppressive drugs mediated by specific bacterial species and enzymes.

The paper investigates how gut microbiota modify steroidal alkaloids from Solanum plants, affecting host exposure and physiological effects.

SimMiL simulates longitudinal microbiome data to assess statistical tools for microbiome analysis, showing it can replicate Type I error and power analyses of existing methods.

This paper introduces a non-black-box method to classify ecological time series pairs in mouse gut microbiota, revealing significant correlations despite many zeros and non-stationarity.

This study shows that Limosilactobacillus reuteri from tamely bred mice increases tameness and oxytocin levels when administered, suggesting a role in domestication.

This study identifies Eggerthella lenta as a key gut bacterium that enhances resveratrol's efficacy through reductive metabolism, producing a more active metabolite.

This study identifies genetic loci linking host amylase genes to gut microbiome composition and metabolic traits in hyperlipidemic mice.

The paper designs a synthetic microbiome that suppresses gut pathogens using a statistical approach, showing it effectively clears Kp-MH258 in multiple environments.

This study uses C. elegans to screen human gut microbiota for colonization and resistance against C. difficile, finding 46% colonization success and 50% in vivo inhibition of C. difficile.

A defined consortium of early-life microbes shapes immune development and prevents type 1 diabetes.