Daniel R. Noguera

The paper analyzes metagenomes and metagenome-assembled genomes from microbial communities in a wastewater treatment plant under varying dissolved oxygen conditions to understand microbial adaptation to low-DO environments.

The paper analyzes metagenomes and MAGs from a wastewater treatment plant under varying DO conditions to study microbial adaptation to energy-efficient processes.

The paper introduces TbasCO, a trait-based comparative omics approach that identifies ecosystem-level and niche-differentiating adaptations in microbial communities using genome-resolved time-series metatranscriptomics.

The paper uses genome-resolved metatranscriptomics to analyze gene expression differences among co-occurring Accumulibacter clades in a wastewater treatment bioreactor, revealing functional distinctions.

The paper integrates metagenomic, metatranscriptomic, and thermodynamic analyses to predict and characterize the metabolic network of an anaerobic microbiome producing medium-chain fatty acids from renewable feedstock.