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Chinese Journal of Experimental and Clinical Infectious Diseases(Electronic Edition) ›› 2023, Vol. 17 ›› Issue (03): 164-172. doi: 10.3877/cma.j.issn.1674-1358.2023.03.004

• Research Article • Previous Articles     Next Articles

Microbiota characteristics of urine microbiota in patients with diabetic urinary tract infection based on 16S rRNA gene sequencing analysis

Jiuhu Yin, Xiaoming Lu, Ke Sun, Zhongquan Yi, Yuanyuan Shen, Yadong Liu()   

  1. Department of Urology, The Third People’s Hospital of Yancheng, Yancheng 224000, China; Department of Central Laboratory, The Third People’s Hospital of Yancheng, Yancheng 224000, China
    Department of Urology, The Third People’s Hospital of Yancheng, Yancheng 224000, China; Yancheng Hospital, the Affiliated Hospital of Jiangsu Vocational College of Medicine;, Yancheng 224000, China
    Department of Endocrinology and Metabolic Diseases, The Third People’s Hospital of Yancheng, Yancheng 224000, China
    Department of Urology, The Third People’s Hospital of Yancheng, Yancheng 224000, China
    Department of Urology, The Third People’s Hospital of Yancheng, Yancheng 224000, China; Department of Central Laboratory, The Third People’s Hospital of Yancheng, Yancheng 224000, China; Yancheng Hospital, the Affiliated Hospital of Jiangsu Vocational College of Medicine;, Yancheng 224000, China
  • Received:2022-12-01 Online:2023-06-15 Published:2023-08-22
  • Contact: Yadong Liu

Abstract:

Objective

To explore the application of 16S rRNA sequencing on analysis of the microbiota characteristics of urine flora in diabetic urinary tract infections.

Methods

The urine samples of patients with diabetic urinary tract infection (DI) (12 cases), patients with diabetic non-urinary tract infection (DNI) (12 cases), normal population (NOR) (9 cases) and patients with urinary tract infection (UTI) (7 cases) were collected from outpatients and inpatients in the Department of Urology and Endocrinology of the Third People’s Hospital of Yancheng from March 2021 to September 2021, and were sequenced and analyzed by the conserved region V3 and V4 of 16S rDNA. The indices Alpha was used to analyze the abundance and evenness of urine microbiota. The flora species composition of different groups was analyzed by beta diversity, and the heat map of correlation between the flora was drawn by R software. The phenotypes of different groups were forecasted by BugBase software.

Results

In Alpha diversity analysis, there were significant differences in observed species, shannon, simpson, chao1 between DI group and NOR group (t = 2.833, P = 0.011; t = 3.619, P = 0.002; t = 2.82, P = 0.011; t = 2.69, P = 0.017). In Beta diversity comparison, PCoA analysis showed no significant difference among the four groups (F = 1.71, P = 0.071), while patients in DI group and DNI group had significant difference in PCoA analysis (F = 2.56, P = 0.031). During the analysis of species composition, at the phylum level, Firmicutes were significantly different between DI group and DNI group (Z =-2.425, P = 0.014). At the genus level, 3 genera including Lactobacillus, Negativicoccus, Rikenella showed significant differences in the urine samples between DI group and DNI group (Z =-2.175, P = 0.03; Z =-2.685, P = 0.007; Z =-2.134, P = 0.033). Total of 14 genera including Porphyromonas were significantly different between DI group and NOR group (all P < 0.05). Vulcaniibacterium were significantly different in the urine samples of DI group and UTI group (Z =-2.405, P = 0.019). In the analysis of microbiota correlation, Proteobacteria were negatively correlated with Actinobacteria (r =-0.73, P = 0.007) and Firmicutes (r =-0.67, P = 0.017) in DI group. In the study of microbiota phenotype, biofilm formation phenotype were significantly different between DI group and DNI group (Z =-2.456, P = 0.014).

Conclusions

The abundance and evenness of microbiota in DI group were significantly lower than those in NOR group. The imbalance of Proteobacteria, Actinomycetes and Firmicutes may lead to differences in biofilm formation phenotypes, and thus increase the susceptibility to urinary tract infections of diabetic patients.

Key words: Diabetes mellitus, Urinary tract infection, Microbiota, 16S rRNA

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