Methodological bias shapes the interpretation of the urinary microbiome in low-biomass systems
TL;DR
How factors such as sample collection methods, contamination dynamics, DNA extraction protocols, sequencing approaches, and bioinformatic pipelines shape microbial profiles and contribute to inconsistencies in microbiome–disease associations is examined.
Abstract
The recognition of the urinary microbiome (urobiome) has challenged the long-standing paradigm of urinary tract sterility, revealing diverse microbial communities associated with both urinary health and disease. However, the characterization of the urobiome remains highly variable across studies, particularly due to the low-biomass nature of urine samples and the strong influence of methodological bias. In this Mini Review, we examine how factors such as sample collection methods, contamination dynamics, DNA extraction protocols, sequencing approaches, and bioinformatic pipelines shape microbial profiles and contribute to inconsistencies in microbiome–disease associations. We further discuss the limitations of traditional culture-based diagnostics, which fail to detect many microorganisms identified through sequencing-based approaches, and highlight the need for standardized, contamination-aware, and function-oriented frameworks. Finally, we explore the potential of integrated multi-omics strategies to improve the reliability, reproducibility, and clinical relevance of urobiome research in urinary tract health and disease.