Johannes Zimmermann

This study identifies predatory bacteria (BALOs) in the human gut microbiome, showing they enhance microbial diversity and may contribute to gut homeostasis by controlling harmful bacteria.

This study shows predatory bacteria alter C. elegans microbiota, increasing vitamin B12 availability, which extends lifespan by suppressing a detoxification pathway.

This paper uses multi-omic profiling in a mouse stroke model to show that host and microbial changes converge around day 7 post-injury.

The paper introduces Virtual Colon, a spatiotemporal metabolic model of the colon that simulates host-microbial interactions and visualizes them over time and space.

The paper investigates how microbial communities adapt metabolically in different environments, showing changes in carbon usage, biosynthesis, and interactions across monocultures, in vitro communities, and the mouse gut.

This paper uses metatranscriptomics and metabolic modeling to analyze patient-specific urinary microbiomes during infection, identifying metabolic dependencies and potential interventions for antibiotic-resistant UTIs.

The paper integrates multi-omics data from mice to identify molecular features linked to aging-related cognitive decline, highlighting systemic inflammation and microbiome-driven gut-brain axis dysfunction.

This study uses metabolic modeling to uncover host-microbiome metabolic dysregulation in IBD, identifying key pathways and potential therapeutic interventions.

This study uses multi-omics and metabolic modeling in mice to show that aging reduces host-microbiome metabolic interactions, affecting key host pathways involved in intestinal barrier function and homeostasis.

The paper characterizes new Pseudobdellovibrionaceae strains, revealing genomic features and evolutionary insights into bacterial predation modes.

The paper uses metabolic modeling to predict precision prebiotics that specifically enhance the abundance of a beneficial microbiome species in C. elegans.

This study evaluates COBRA-based tools for microbial consortia modeling using FAIR criteria and experimental data, finding that newer, better-documented tools generally outperform older ones in quality and performance.

gapseq predicts bacterial metabolic pathways and reconstructs metabolic models with high accuracy using sequence homology and pathway topology, outperforming existing tools.