Justin Laine Sonnenburg

The paper engineers a gut bacterium to enhance osmotic resistance, enabling it to survive malabsorption in industrialized microbiomes.

The paper identifies functional divergence in gut Clostridia from Hadza hunter-gatherers, revealing diet-adapted metabolic pathways that influence gut ecology.

The paper compares gut microbiomes of Tsimane and Hadza populations to show that many microbes co-migrated with humans globally, but are now vanishing in industrialized populations.

The paper tracks gene flow in the gut microbiome, showing diet and community ecology influence phage activation and horizontal gene transfer.

The paper tracks lineage evolution and transmission of Bacteroides thetaiotaomicron across hosts and ecological scales using genomic barcoding and whole-genome sequencing.

The paper examines gut microbiome changes in chronic systolic heart failure patients, linking microbiome alterations to disease severity and clinical improvement.

This study identifies fermentation-derived metabolites (FDMs) from fermented foods that modulate immune, microbial, and metabolic systems to reduce inflammation and metabolic disease severity.

This study shows that gut microbiome recovery after antibiotics is path-dependent, shaped by ecological and evolutionary dynamics including strain sweeps, genetic changes, and phage activity.

Eubiota enables autonomous discovery in the gut microbiome by integrating modular agents and reinforcement learning, identifying key pathways and designing therapeutic interventions.

The paper presents a global virome atlas, UHGV, and identifies genomic factors influencing phage-host interactions.

The paper shows that nutrient competition drives changes in gut microbiome composition under drug perturbations, with implications for predicting and mitigating drug side effects.

MiFoDB is a metagenomics workflow that identifies microbes in fermented foods with high taxonomic resolution, enabling strain tracking and functional analysis.

The paper introduces MIG-Seq to analyze IgA binding to gut microbiome strains and finds that microbial genes, especially mucus degradation genes, predict IgA binding levels.

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 paper introduces a high-throughput stool proteomic pipeline, SHT-Pro, and demonstrates its application in classifying dietary interventions based on proteomic profiles with up to 89% accuracy.