Advances in 16S Taxonomic Classification: Impacts on Species-Level Resolution of Female Bladder Microbiota

Abstract

Bacteria are present in the human urinary bladder, even in the absence of infection. These bacteria comprise the urinary microbiome, or urobiome, and have the potential to promote bladder health or contribute to pathology. Despite its importance, studying the urobiome remains challenging given the high proportion of host to bacterial cells and low microbial biomass. The leading method for studying the urobiome has been 16S rRNA amplicon sequencing. This culture-independent approach provides a cost-effective method for identifying bacteria, but taxonomic classification accuracy depends on three key factors: 1) the variable region targeted; 2) the reference database; and 3) the classification algorithm. In 2021, Hoffman et al. demonstrated that species-level classification of bladder microbiota was possible and that the database used was the most important factor, followed by the variable region. Here, we provide an updated analysis evaluating classification schemes using updated taxonomic databases, most notably GreenGenes2, and expand the analysis to full length 16S gene sequencing. We show that updated taxonomic reference databases improve the ability to identify bladder microbiota at the species level and that long-read sequencing of the full length 16S rRNA gene further improves species identification.