Eric G. Pamer

IDBac provides a centralized database and platform for bacterial identification via MALDI-TOF MS, enabling spectral comparison and analysis of bacterial isolates.

This study shows dietary glutamate influences ImP production via microbial competition, affecting glucose tolerance and systemic ImP levels.

This paper presents a rapid diagnostic test to measure fecal butyrate and deoxycholic acid concentrations as markers of microbiome function, enabling quick identification of patients with microbiome deficiencies.

This study shows lantibiotic-producing bacteria reduce microbiome resilience and increase susceptibility to infections after antibiotic treatment.

The paper uses machine learning to identify valeric acid as a bacterial metabolite that inhibits Candida parapsilosis growth through intracellular acidification, reducing fungal colonization in mice.

This study investigates the effect of dietary fiber on immune checkpoint blockade efficacy in murine tumor models and finds inconsistent results across different models.

This paper shows that an avirulent C. difficile strain, ST1-75, protects mice from virulent strain-induced colitis by outcompeting it through rapid amino acid depletion, suggesting potential as a biotherapeutic for CDI prevention.

The paper characterizes a large collection of Bacteroidales isolates from the human gut, revealing genomic and metabolomic diversity and horizontal gene transfer across species.

The paper characterizes six gut-derived nisin-like lantibiotics, evaluates their antimicrobial activity against pathogens and commensals, and identifies key residues affecting their activity.

This study shows that lantibiotic resistance genes in gut bacteria affect microbiota composition and function, with implications for microbiome health and resistance strategies.

The paper describes bacterial strains in the human gut using a statistical model based on their evolutionary history to predict metabolic phenotypes and engineer consortia.

The paper compiles shotgun metagenomic data from stool samples of hospitalized hematopoietic cell transplant patients to enhance microbiome analysis beyond taxonomic composition.