Gut microbiota and health

The paper shows gut microbiota influences host gene regulation, identifying specific taxa and genes, and demonstrates microbiome manipulation can alter gene expression profiles.

MITRE predicts host status from microbiome time-series data, performing on par or better than black-box methods while maintaining interpretability.

The paper identifies a blood metabolome signature that robustly predicts gut microbiome α-diversity across health and disease conditions.

FlashWeave infers direct microbial interactions from large-scale metagenomic data, outperforming existing methods in speed and accuracy across diverse benchmarks.

This study identifies genetic loci associated with gut microbiota composition and bile acid profiles in mice using QTL analysis and validation experiments.

VOLARE is a web tool that visualizes microbiome-immune system relationships through interactive regression analysis, enabling domain experts to evaluate candidate results for further experimentation.

This study uses 16S rRNA gene sequencing to examine gut microbial changes in 6-OHDA-induced Parkinson's disease mice and finds no significant changes in diversity but altered abundance of specific bacterial species.

The paper introduces MicroPro, a metagenomic analysis tool that improves disease association predictions by including reads from unknown organisms, and identifies new microbial and viral associations with colorectal cancer, type-2 diabetes, and liver cirrhosis.

The paper introduces a computational method to cluster microbial genes by co-abundance, identifying reproducible gene groups linked to colorectal cancer and inflammatory bowel disease.

This study performs a meta-analysis of gut metagenomes to identify microbiome features associated with health and disease across multiple conditions.

This study investigates the association between APOE genotype and gut microbiome composition in humans and APOE-TR mice, finding specific microbial and metabolic differences linked to APOE alleles.

The paper shows that human AMY1 gene copy number affects oral and gut microbiome composition and function, with low-AMY1 associated with enhanced complex carbohydrate breakdown and high-AMY1 linked to resistant starch fermentation and higher adiposity.

ENIGMA identifies microbial associations with disease by estimating enterotype-like clusters and environmental effects using a probabilistic model.

The paper uses metaproteomics to analyze cecum contents in CKD rats with and without resistant starch, revealing shifts in gut microbiota and host proteins associated with improved CKD outcomes.

The paper identifies BSH gene distribution and activity patterns across 11 human populations, revealing phylotype abundance and enzyme activity differences.

HMP16SData provides integrated 16S rRNA sequencing data from the Human Microbiome Project, enabling easier analysis for researchers with basic R skills.

This study analyzes gut microbiota differences between healthy adults and chronic traumatic complete SCI patients, finding dysbiosis linked to serum biomarkers and neurogenic bowel dysfunction.

This study shows that intermittent HFHS diet in rats reduces social interaction, impairs memory, and alters gene expression and microbiota, with specific taxa linked to these changes.

The paper develops a modeling framework to analyze microbiota dynamics in artificial human guts, revealing technical noise as a major source of variation and identifying sub-daily fluctuations and replicable trajectories.

Knomics-Biota provides a web-based tool for exploratory analysis of human gut metagenomic data, enabling users to generate reports and visualize microbiota composition in relation to experimental factors and public datasets.

The paper examines co-occurrence patterns of gut and respiratory microbiota in pre- and full-term infants over the first year, identifying three patterns of CST manifestation related to infant maturity.

The paper studies synthetic gut communities to understand species interactions and emergent behavior through culturing, modeling, and transcriptomics.

The paper analyzes the facial and gut microbiomes of vultures to identify microbial elements that contribute to their adaptation to scavenging diets.

The paper identifies microbial genes associated with gut colonization and disease by using phylogenetic correction in metagenomic data analysis.

The paper introduces a new method for microbiome analysis that identifies balances between groups of taxa instead of testing individual taxa, improving the interpretation of compositional data.

The paper develops a model-guided framework to predict microbial interactions in synthetic human gut microbiome communities and identifies key ecological drivers and network design principles.

The paper introduces a method to quantify and evaluate co-exclusion patterns in microbial communities and applies it to human microbiome data.

The paper investigates the relationship between miRNA expression in CRC tissues and microbiome composition, identifying miRNAs correlated with bacterial taxa and suggesting potential therapeutic targets.

The paper investigates how propionate, a gut microbial metabolite, interacts with the blood-brain barrier through CD14-dependent and NRF2 signaling pathways, suggesting a new mechanism in the gut-brain axis.