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The impact of urine microbiota in patients with lower urinary tract symptoms

  • Hsiang-Ying Lee,
  • Jiunn‐Wei Wang,
  • Yung-Shun Juan,
  • Ching-Chia Li,
  • Chung-Jung Liu,
  • Sung Yong Cho,
  • Hsin-Chih Yeh,
  • Kuang-Shun Chueh,
  • Wen-Jeng Wu,
  • Deng‐Chyang Wu

Publication: Annals of Clinical Microbiology and Antimicrobials, April 2021

Introduction

Inflammation and infection are causative factors of benign prostatic hyperplasia (BPH). Urine is not sterile, and urine microbiota identified by DNA sequencing can play an important role in the development of BPH and can influence the severity of lower urinary tract symptoms (LUTS).

Materials and methods

We collected mid-stream voided urine samples from BPH patients and control participants and stored them in a freezer at − 80 °C. All enrolled participants were requested to provide information about their clinical characteristics and complete the International Prostate Symptom Score (IPSS) questionnaire. Each step of the procedure, including the extraction of the genomic DNA from the urine samples; the amplification by polymerase chain reaction (PCR); PCR product quantification, mixing, and purification; DNA library preparation; and sequencing was performed with quality control (QC) measures. Alpha diversity was indicative of the species complexity within individual urine samples, and beta diversity analysis was used to evaluate the differences among the samples in terms of species complexity. Pearson’s correlation analysis was performed to calculate the relationship between the clinical characteristics of the participants and the microbiota species in the urine samples.

Results

We enrolled 77 BPH patients and 30 control participants who reported no recent antibiotic usage. Old age, high IPSS and poor quality of life were observed in the participants of the BPH group. No significant differences were observed in the alpha diversity of the samples. In the beta diversity analysis, there was a significant difference between the microbiota in the samples of the BPH and control groups according to ANOSIM statistical analysis. On comparing the groups, the ten bacterial genera present in the samples of the BPH group in descending order of abundance were: Sphingomonas, Bacteroides, Lactobacillus, Streptococcus, Alcaligenes, Prevotella, Ruminococcaceae UCG-014, Escherichia_Shigella, Akkermansia, and Parabacteroides. Spearman’s correlation analysis revealed that urine samples showing the presence of the bacterial genera Haemophilus, Staphylococcus, Dolosigranulum, Listeria, Phascolarctobacterium, Enhydrobacter, Bacillus, [Ruminococcus]torques, Faecalibacterium, and Finegoldia correlated with a high IPSS, and severe storage and voiding symptoms (P < 0.05).

Conclusion

Our current study shows that dysbiosis of urine microbiota may be related to the development of BPH and the severity of LUTS. Further research targeting specific microbes to identify their role in the development of diseases is necessary and might provide novel diagnostic biomarkers and therapeutic options.