Martin J. Blaser

This study shows milk urea increases during lactation, is conserved across mammals, and supports infant gut microbiome establishment through urea-metabolizing bacteria.

This study identifies epigenetic phase variation in the gut microbiome, showing it enhances bacterial adaptation through gene regulation and bet-hedging strategies.

A gut consumer-resource model with explicit metabolic pathways yields competition-dominated healthy and cooperation-dominated dysbiotic states; an interaction-balance index (ENBI) detects this shift in human disease cohorts.

PRISM improves microbial analysis in low-biomass sequencing data, identifies tumor-associated microbes in cancer datasets, and reveals potential clinical significance.

This study shows that early-life H. pylori infection in mice increases visceral adiposity and alters endocrine and inflammatory responses to high-fat feeding.

This study shows that the 16p11.2 microdeletion worsens neurodevelopmental issues caused by early-life antibiotic exposure, affecting gut microbiota, hippocampal development, and behavior.

The paper identifies microbially-produced phospholipids that reduce inflammation and counteract antibiotic-induced type 1 diabetes in mice, with similar effects observed in humans.

SAHMI identifies microbial nucleic acids in mammalian tissues and filters contaminants, enabling co-detection of somatic cells and microorganisms in single-cell and spatial genomic data.

ARZIMM infers microbial interactions and community stability from longitudinal microbiome data using a zero-inflated mixed-effects model.

The paper introduces a microbial trend analysis framework to characterize dynamic microbial patterns in longitudinal studies, showing its effectiveness in trend detection, group comparison, and classification.

The paper introduces JointMM, a joint modeling framework for analyzing longitudinal microbiome proportions and time-to-event data, showing its effectiveness in identifying microbial associations with disease progression.

The paper estimates molecular clock rates in Campylobacter using a birthday problem analogy to quantify lineage turnover and diversification in environmental bacteria.

The paper introduces a causal mediation model for high-dimensional microbiome data to estimate and test microbial causal effects in a three-factor study design.