Nazema Y. Siddiqui

The paper evaluates updated 16S rRNA sequencing methods and databases for improved species-level classification of the urinary microbiome.

The paper examines how vaginal estrogen affects the urinary microbiome and metabolome in postmenopausal women, finding that it increases lactobacilli and alters metabolite profiles.

The paper identifies a mechanism by which commensal bacteria inhibit viral infections through a tryptophan metabolite that activates the aryl hydrocarbon receptor.

The paper introduces a negative binomial latent factor model for paired microbiome data to account for cross-site correlations and improve statistical analysis of microbial compositions.

This study shows species-level identification of bladder bacteria is possible using 16S rRNA amplicon sequencing by optimizing reference databases and variable regions.