The TRACS algorithm tracks bacteria, viruses and parasites in metagenomic or population sequencing data, detecting microbial transmission even when multiple strains coexist within a host.

Nature Protocols, Published online: 06 August 2025; doi:10.1038/s41596-025-01239-4This protocol uses the R microeco package to provide a pipeline for the statistical analysis and visualization of microbiome data, covering omics data types such as amplicon sequencing data, metagenomic sequencing data and nontargeted metabolomics data.

From the NY Fed: Household Debt Rose Modestly; Delinquency Rates Remain Elevated The Federal Reserve Bank of New York’s Center for Microeco...

It is commonly thought that bacterial species borders tend to be fuzzy, due to frequent exchange of DNA. Here, Diop et al. quantify the patterns of gene flow between core genomes across 50 major bacte...

The current version 2.0 of the microeco package represents a substantial update compared to the previously published version. Key enhancements include the addition of new classes, integration of a br...

Application for UEF Summer School courses will begin February 1st, 2025. The application deadline is June 1st, 2025. Click here to go to the application…

Marine bacteria opt for divergent foraging strategies when faced with carbon starvation—either cease motility entirely, or convert biomass to energy to retain motility.

Soil microbial ecology is increasingly recognized as essential to climate mitigation, but realizing its full potential requires shifting from static genome inventories to dynamic assessments of microbial activity. This study shows that methane-cycling microbes exhibit stable, depth-stratified expression patterns, even in response to major redox and flooding shifts, undermining assumptions that water-table manipulations common in wetland management can alone reduce methanogenesis. Instead, methane cycling is shaped by spatially organized, transcriptionally active networks involving not only methanogens but also methanotrophs, fermenters, and iron reducers. These findings expose the limitations of genome-only models and highlight the need for soil diagnostics that capture in situ activity. Together, we provide a foundation for developing activity-based microbiome tools, embedding microbial functions into Earth system models, and designing interventions that move beyond “single-lever” strategies and instead work with the structure and dynamics of microbial communities as complex, layered systems.

Studying microbial community dynamics is fundamental to better understand ecosystem stability, resilience and environmental change. Community composition changes with the growth of individual members,...

This is our ninth blog post for our Job Market Paper Series blog for 2024-2025. Sakina Shibuya is an applied economics Ph.D. candidate at University of Wisconsin-Madison. She is an applied microeco…