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Background <p>Knowledge of the urinary microbiome (urobiome) in diabetic kidney disease (DKD) remains limited. The most commonly used 16S rRNA sequencing technique can only provide bacterial identification at the genus level. As a novel technique, 2bRAD sequencing for microbiome (2bRAD-M) can be used to identify the low-biomass microbiome at the species level. In this study, we used 2bRAD-M to compare the urobiome composition of patients with DKD at different stages with healthy individuals and those with type 2 diabetes mellitus (T2DM), with the expectation that we would find discriminative species correlated with DKD.</p> Method <p>Healthy controls, patients with DKD with microalbuminuria (DKD1 group) or macroalbuminuria (DKD2 group), and patients with T2DM were recruited (n = 20 for each group). The first-morning urine was collected for 2bRAD-M testing. The albumin-to-creatinine ratio (ACR) was also measured with urine samples. Serum samples were collected for detecting clinical indicators. The microbial diversity and composition based on abundance were calculated. Differential bacteria for different groups were identified. Besides, the correlation between discriminative bacteria and clinical indices was also analyzed.</p> Results <p>Urobiome diversity was significantly reduced in the DKD groups. In the DKD1 group, was the dominant genus, followed by <i>Pseudomonas_E</i>, whereas in the DKD2 group, <i>Pseudomonas_E</i> became the dominant genus and <i>Escherichia</i> was notably reduced. Both <i>Bifidobacterium</i> and <i>Streptococcus</i>, which were the top genera in the control group, were substantially decreased in the DKD groups. The discriminative species for DKD1 included <i>Escherichia coli</i> and <i>Acinetobacter johnsonii</i>, while for DKD2, <i>Pseudomonas_E oleovorans</i>, <i>Enterococcus faecalis</i>, and <i>Morganella morganii</i> were identified. <i>Pseudomonas_E</i>, <i>Enterococcus</i> and <i>Morganella</i> showed a strong correlation with renal function indicators and urinary protein levels.</p> Conclusion <p>The urobiome diversity and composition in patients with DKD were markedly different from those in healthy individuals and T2DM patients. These findings provide valuable insights into the onset and progression of DKD, driven by changes in the urinary bacterial community structure.</p>

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Urobiome of patients with diabetic kidney disease in different stages is revealed by 2bRAD-M

  • 期刊论文

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  • 发表日期：

    2025年4月10日

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  • Nan Li,
  • Ying Wang,
  • Haojun Zhang,
  • Liang Ma,
  • Xinhui Huang,
  • Yuhang Qiao,
  • Han Li,
  • Hailing Zhao,
  • Ping Li

摘要

Background

Knowledge of the urinary microbiome (urobiome) in diabetic kidney disease (DKD) remains limited. The most commonly used 16S rRNA sequencing technique can only provide bacterial identification at the genus level. As a novel technique, 2bRAD sequencing for microbiome (2bRAD-M) can be used to identify the low-biomass microbiome at the species level. In this study, we used 2bRAD-M to compare the urobiome composition of patients with DKD at different stages with healthy individuals and those with type 2 diabetes mellitus (T2DM), with the expectation that we would find discriminative species correlated with DKD.

Method

Healthy controls, patients with DKD with microalbuminuria (DKD1 group) or macroalbuminuria (DKD2 group), and patients with T2DM were recruited (n = 20 for each group). The first-morning urine was collected for 2bRAD-M testing. The albumin-to-creatinine ratio (ACR) was also measured with urine samples. Serum samples were collected for detecting clinical indicators. The microbial diversity and composition based on abundance were calculated. Differential bacteria for different groups were identified. Besides, the correlation between discriminative bacteria and clinical indices was also analyzed.

Results

Urobiome diversity was significantly reduced in the DKD groups. In the DKD1 group, was the dominant genus, followed by Pseudomonas_E, whereas in the DKD2 group, Pseudomonas_E became the dominant genus and Escherichia was notably reduced. Both Bifidobacterium and Streptococcus, which were the top genera in the control group, were substantially decreased in the DKD groups. The discriminative species for DKD1 included Escherichia coli and Acinetobacter johnsonii, while for DKD2, Pseudomonas_E oleovorans, Enterococcus faecalis, and Morganella morganii were identified. Pseudomonas_E, Enterococcus and Morganella showed a strong correlation with renal function indicators and urinary protein levels.

Conclusion

The urobiome diversity and composition in patients with DKD were markedly different from those in healthy individuals and T2DM patients. These findings provide valuable insights into the onset and progression of DKD, driven by changes in the urinary bacterial community structure.