Analysis of Urinary Flora Characteristics in Urinary Tumor Based on 16S rRNA Sequence.

Abstract

The relationship between urinary system tumors and urothelial microorganisms remains unexplored. This study is aimed at exploring the relationship between urinary flora and urinary tumors and identifying potential biomarkers for urinary tumors and new targets for prevention. We included four healthy adults (control group) and six patients diagnosed with urinary tract tumors (tumor group). In both groups, 10 and 50 ml clean middle urine samples were reserved. The 10 ml samples were analyzed (including pH, specific gravity, and leukocytes) using an automatic urine analyzer, and the 50 ml samples were analyzed by DNA extraction, 16S rRNA gene amplification, and high-throughput sequencing. The correlation between routine urine analysis and sequencing results was also analyzed. Testing using the DESeq2 method showed that, at the order level, there were significant differences in the abundance of Caulobacterales between the urinary flora of the two groups (P < 0.05); family level, Bacteroidaceae, Actinomycetaceae, and Tsukamurellaceae (P < 0.05); genus level, Finegoldia, Varibaculum, Actinobaculum, Propionimicrobium, Bacteroides, Brevundimonas, and Tsukamurella (P < 0.05). LEfSe analysis found specific bacteria at the genus level in the urinary flora of the tumor group, namely, Finegoldia (genus Digestiflora) (P < 0.001) and Varibaculum (P < 0.001). Further correlation analysis showed that both species were positively correlated with the urine pH (P < 0.05). PICRUSt analysis showed significant differences in the two functional pathways of cell transformation and metabolism (P < 0.05). Combined with the results of bioinformatics analysis, some differential bacteria may be new biomarkers for urologic tumors, and there may be a correlation between urine pH and tumor occurrence. However, large-scale prospective studies and in vitro and in vivo experiments are required to further test and verify these findings.