肾结石病(KSD)的发病机制尚不完全清楚,和潜在的影响因素仍有待探索。几项研究表明,使用16SrRNA基因测序,结石形成者的尿微生物组(尿菌组)与健康个体不同,其中大多数仅在属水平上提供微生物鉴定。微生物组的2bRAD测序(2bRAD-M)是一种新颖的测序技术,能够在物种分辨率下准确表征低生物量微生物组。我们旨在应用2bRAD-M对单侧肾结石患者的肾盂尿路生物群进行分析,并比较有无结石的尿路生物群。
共招募了30例单侧结石患者,从两侧收集肾盂尿液。将输尿管镜与结石一起插入肾盂,并将输尿管导管置于输尿管镜中以收集肾盂尿。用新装置再次重复该过程以收集另一侧的尿液。进行2bRAD-M以表征单侧结石形成者的肾盂尿路生物群,以探索结石侧和非结石侧之间是否存在微生物差异。
石侧的微生物群落组成与非石侧的微生物群落组成相似。配对比较表明,结石侧棒状杆菌增加,普雷沃氏菌和乳酸菌减少。四种(普雷沃氏菌,乳酸菌,金黄色棒状杆菌,假单胞菌sp_286)在非结石侧代表过多。还通过线性判别分析效应大小(LEfSe)在两组之间鉴定了24个差异分类单元。在相关分析中观察到属种之间广泛而紧密的联系。此外,使用特定的富集物种构建随机森林分类器,可以区分石侧和非石侧,准确率为71.2%。
第一次2bRAD-M微生物组调查提供了一个重要的提示,提示尿路菌群失调在KSD中的潜在作用,并提供了对结石形成机制的更好理解。
The pathogenesis of kidney stone disease (KSD) is not fully understood, and potential contributing factors remain to be explored. Several studies have revealed that the urinary microbiome (
urobiome) of stone formers was distinct from that of healthy individuals using 16S rRNA gene sequencing, most of which only provided microbial identification at the genus level. 2bRAD sequencing for Microbiome (2bRAD-M) is a novel sequencing technique that enables accurate characterization of the low-biomass microbiome at the species resolution. We aimed to apply 2bRAD-M to profile the renal pelvis
urobiome of unilateral kidney stone patients and compared the
urobiome with and without stone(s).
A total of 30 patients with unilateral stones were recruited, and their renal pelvis urine from both sides was collected. A ureteroscope was inserted into the renal pelvis with stone(s) and a ureteral catheter was placed into the ureteroscope to collect renal pelvis urine. This procedure was repeated again with new devices to collect the urine of the other side. 2bRAD-M was performed to characterize the renal pelvis
urobiome of unilateral stone formers to explore whether microbial differences existed between the stone side and the non-stone side.
The microbial community composition of the stone side was similar to that of the non-stone side. Paired comparison showed that Corynebacterium was increased and Prevotella and Lactobacillus were decreased in the stone side. Four species (Prevotella bivia, Lactobacillus iners, Corynebacterium aurimucosum, and Pseudomonas sp_286) were overrepresented in the non-stone side. 24 differential taxa were also identified between two groups by linear discriminant analysis effect size (LEfSe). Extensive and close connections among genera and species were observed in the correlation analysis. Moreover, a random forest classifier was constructed using specific enriched species, which can distinguish the stone side from the non-stone side with an accuracy of 71.2%.
This first 2bRAD-M microbiome survey gave an important hint towards the potential role of urinary dysbiosis in KSD and provided a better understanding of mechanism of stone formation.