Christoph Kaleta

This study shows that PPI-associated microbiome changes cause systemic metabolic and transcriptional responses, affecting metabolism and inflammation in multiple tissues.

This study examines gut microbiome diversity and structure across different lifestyles in Thailand, finding variations in microbial composition and associations with lifestyle factors.

This study identifies nonlinear gene-expression trajectories in the aging male mouse colon, revealing midlife transitions and a transcriptomic clock based on three genes.

The paper examines how two gut microbes interact under bile acid stress, finding that one species helps the other survive by exchanging vitamin B6.

The paper uses genome-scale metabolic models to predict how diet and lifestyle affect microbial interactions in the gut microbiome, finding shifts from collaboration to competition with high sugar intake.

This study shows that specific metabolites can shift Hydra's microbiome composition and function, leading to ammonia toxicity and disease-like phenotypes.

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.

The paper identifies sphingolipids from a bacterial PKS as mediators of microbiota protection against pathogens in C. elegans.

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

This study uses metabolic modeling to show that type 2 diabetic gut microbiota show increased autonomy and antagonism, with reduced host-microbiome metabolite exchange.

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.

This study shows that deleting HKDC1 in intestinal epithelial cells reduces tumor growth and protects against colorectal cancer in mice by impairing mitochondrial function and cell proliferation.

The paper examines the relationship between HK2 expression and inflammation severity in IBD patients using bulk transcriptome data and confirms findings at the cellular and protein levels.

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

This study shows that E. coli evolves specific genetic and phenotypic traits in an inflamed gut, leading to antibiotic collateral sensitivity and potential therapeutic implications.

This study uses dynamic optimization to analyze host-pathogen interactions in invasive aspergillosis, identifying key roles for epithelial cells and neutrophils in immune response and fungal virulence.

The paper identifies toxic intermediates in fungal metabolic pathways as potential antifungal targets using a random forest model and provides a web-service for exploration.

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