Christian Diener

The paper develops metaSPLiT, a single-cell RNA sequencing method, to reveal sub-species functional specialization in the human gut microbiome.

MICOMWeb provides a user-friendly platform for microbial community metabolic modeling of the human gut, addressing challenges in computational infrastructure and user expertise.

This paper estimates absolute bacterial biomass in the gut using host-derived read normalization from metagenomic data, showing it tracks antibiotic treatment response in mice and humans.

This study identifies Methanobrevibacter smithii as associated with colorectal cancer through trophic interactions with CRC-causing bacteria and archaeal-derived compounds.

This paper introduces MEDI, a method to estimate dietary intake from stool metagenomes by analyzing food-derived DNA, showing accurate detection of food items and prediction of dietary patterns.

The paper develops a cell-type-specific genome-scale metabolic model of human colonic epithelial cells to identify metabolic signatures associated with inflammatory bowel disease.

This study identifies cachexia-associated microbial metabolites using computational modeling and metabolomic analyses in a murine cancer model.

This study identifies gut microbiota interactions that inhibit C. difficile strains across nutrient environments, highlighting strain variability and nutrient context as key factors.

This study shows that long-term NMN treatment improves healthspan and extends lifespan in female mice but not males, with sex-specific effects on metabolism and microbiome.

The paper uses microbial community-scale metabolic models to predict C. difficile engraftment risk and assess probiotic therapy efficacy in the human gut.

The paper examines the link between bowel movement frequency and blood metabolites in healthy individuals, finding associations with kidney function and chronic disease risk.

This paper uses microbial community-scale metabolic modeling to predict individual-specific short chain fatty acid production profiles in the human gut and links these predictions to clinical health markers.

The paper analyzes the genetic and microbiome contributions to blood metabolite variation across 2,049 individuals, finding that over 60% of metabolites are associated with either genetics or the microbiome, with some showing interaction effects.

The paper identifies a non-responder phenotype in the murine gut microbiome that exhibits resistance to cefoperazone, showing upregulated antimicrobial resistance genes and reduced central metabolism during antibiotic treatment.

The paper shows that gut microbiome uniqueness increases with age and predicts survival in humans.

The paper identifies gut microbiome biomarkers associated with T2D progression in a Mexican cohort and shows metformin treatment reverses these changes.

Memote, open-source Python software, runs a community-maintained, partly scored test suite (consistency, biomass, annotations, optional experimental data) on SBML-encoded genome-scale metabolic models, once or through continuous integration.

MICOM models gut microbiota metabolism to predict individual-specific short chain fatty acid production and interactions, showing differences between healthy and diabetic subjects.