Evidence map›Paper›PMID 41039187›Full record

ArticleBMC microbiology2025

Revealing the potential value of urine microbiota in ureteral stent encrustation after renal transplantation via Illumina sequencing of 16S rRNA genes.

Juan Chen, Wenjun Song, Shi Yan, Long He, Qing Liu

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Article in BMC microbiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Juan ChenDepartment of Oncology, General Hospital of Northern Theater Command, Shenyang, China.
Wenjun SongDepartment of Urology, Shenyang Red Cross Hospital, No.389 Zhongshan Road, Shenhe District, Shenyang, 110000, China.
Shi YanDepartment of Urology, Shenyang Red Cross Hospital, No.389 Zhongshan Road, Shenhe District, Shenyang, 110000, China.
Long HeOrgan transplantation center, General Hospital of Northern Theater Command, No. 83 Wenhua Road, Shenhe District, Shenyang, 110000, China. helongyh@163.com.
Qing LiuDepartment of Urology, Shenyang Red Cross Hospital, No.389 Zhongshan Road, Shenhe District, Shenyang, 110000, China. liuqing_hongshizhi@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe complication of ureteral stent encrustation (USE) has brought many challenges and troubles to clinical treatment after renal transplantation. The aim of this study was to explore the microbiota that may be involved in the formation and progression of encrustation in ureteral stents.

methodsIn total, 15 patients with ureteral stent non-encrustation (USNE) after renal transplantation and 18 patients with USE after renal transplantation were included in this study. The urine microbiota was analyzed by 16 S rRNA gene sequencing, followed by composition analysis, difference analysis and PICRUSt function prediction. In addition, random forest classification diagnostic models were constructed based on urine microbiota.

resultsCompared to the USNE-U group, the microbial community diversity, evenness, and coverage of the USE-U group were significantly reduced. At the phylum level, Actinobacteriota, Patescibacteria and Desulfobacterota may be the important microbiota involved in the formation of USE. At the genus level, Staphylococcus, Escherichia-Shigella, Dermabacter, Corynebacterium and Streptococcus may play an important role in USE. The functions of microbiota that may be involved in USE formation were also discovered, such as defense mechanisms, amino acid transport and metabolism, and L-rhamnose degradation I. In addition, the receiver operator characteristic (ROC) result showed that the classification model had excellent diagnostic accuracy in detecting USE.

conclusionThe results of this study suggest that urine microbiota may be closely related to the formation of USE, which provides a new perspective for understanding the pathogenesis of USE, which may contribute to early clinical diagnosis and treatment of USE.

Indexed as

BacteriaKidney TransplantationMicrobiotaStentsUrineAdultAgedDNA, BacterialFemaleHigh-Throughput Nucleotide SequencingHumansMaleMiddle AgedPhylogenyRNA, Ribosomal, 16SSequence Analysis, DNADNA, BacterialRNA, Ribosomal, 16S16S rRNAClassification modelFunctional predictionMicrobiotaUreteral stent encrustationUrine

Identifiers

PMID41039187
PMCPMC12492672

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.