Katherine Louie

This study examines how two transgenic sorghum lines with different bioenergy traits affect their rhizosphere microbiome composition and function.

SoLD, a leaf lipidomics resource (244 species) for the Sorghum Association Panel across two field trials, reveals low-input sulfoquinovosyldiacylglycerol depletion, triacylglycerol enrichment, and environment-specific GWAS loci.

The paper introduces a Bayesian Personalized Ranking model to predict microbial substrate preferences and develops an agent that integrates this model with a growth model and LLM for autonomous microbial analysis.

This study shows that desiccation-induced dormancy in Arthrobacter sp. AZCC_0090 preserves mRNA and metabolite profiles, with changes only occurring during drying and rehydration transitions.

This study shows that transgenic rice genotypes overexpressing PSY genes reduce methane emissions by altering rhizosphere microbial hydrogen cycling through changes in gene activity and metabolic pathways.

This study identifies strain-specific functional diversity in Streptomyces endophytes under drought stress, showing enrichment does not correlate with plant growth promotion.

This study shows that co-culturing xylarialean fungi increases metabolite diversity and bioactivity, suggesting competitive interactions drive secondary metabolism.

This study investigates how plant-bacteria-phage interactions affect nitrogen acquisition and exometabolite composition by comparing phage-lysed and uninfected bacterial necromass.

The paper shows that PM-induced changes in host pyruvate metabolism bypass the PDHc to support lipid production for fungal reproduction.

The paper studies how a geothermal spring community responds to diurnal stressors, revealing structured biotic interactions across domains of life.

The paper shows that secondary metabolism gene clusters in Xylariales fungi are linked to broader ecological roles and increased gene diversity.

The paper introduces a web-based tool for collaborative analysis of mass spectrometry data, enabling remote inspection, visualization, and analysis of private and public datasets.

MAGI integrates metabolomics and genomics data to improve metabolite identifications and gene annotations by scoring consensus through biochemical reactions.