Department of Urology, Beijing Friendship Hospital, Capital Medical University, Beijing, China.
Beijing Key Laboratory of Tolerance Induction and Organ Protection in Transplantation, Beijing, China.
Front Cell Infect Microbiol. 2022 May 27;12:860201. doi: 10.3389/fcimb.2022.860201. eCollection 2022.
BK polyomavirus infection results in renal allograft dysfunction, and it is important to find methods of prediction and treatment. As a regulator of host immunity, changes in the gut microbiota are associated with a variety of infections. However, the correlation between microbiota dysbiosis and posttransplant BK polyomavirus infection was rarely studied. Thus, this study aimed to characterize the gut microbiota in BK polyomavirus-infected renal transplant recipients in order to explore the biomarkers that might be potential therapeutic targets and establish a prediction model for posttransplant BK polyomavirus infection based on the gut microbiota.
We compared the gut microbial communities of 25 BK polyomavirus-infected renal transplant recipients with 23 characteristic-matched controls, applying the 16S ribosomal RNA gene amplicon sequencing technique.
At the phylum level, / ratio significantly increased in the BK polyomavirus group. was positively correlated with CD4/CD8 ratio. In the top 20 dominant genera, and exhibited a significant difference between the two groups. No significant difference was observed in microbial alpha diversity. Beta diversity revealed a significant difference between the two groups. Nine distinguishing bacterial taxa were discovered between the two groups. We established a random forest model using genus taxa to predict BK polyomavirus infectious status, which achieved the best accuracy (80.71%) with an area under the curve of 0.82. Two genera were included in the best model, which were and .
BK polyomavirus-infected patients had gut microbiota dysbiosis in which the / ratio increased in the course of the viral infection. Nine distinguishing bacterial taxa might be potential biomarkers of BK polyomavirus infection. The random forest model achieved an accuracy of 80.71% in predicting the BKV infectious status, with and included.
BK 多瘤病毒感染可导致肾移植功能障碍，因此寻找预测和治疗方法非常重要。作为宿主免疫的调节剂，肠道微生物群的变化与多种感染有关。然而，肠道微生物失调与移植后 BK 多瘤病毒感染之间的相关性很少被研究。因此，本研究旨在描述 BK 多瘤病毒感染的肾移植受者的肠道微生物群，以探索可能作为潜在治疗靶点的生物标志物，并基于肠道微生物群建立移植后 BK 多瘤病毒感染的预测模型。
我们应用 16S 核糖体 RNA 基因扩增子测序技术，比较了 25 例 BK 多瘤病毒感染的肾移植受者和 23 例特征匹配对照者的肠道微生物群落。
在门水平上，BK 多瘤病毒组的 / 比值显著增加。与 CD4/CD8 比值呈正相关。在 20 个主要属中，和在两组间存在显著差异。两组间微生物α多样性无显著差异。β多样性显示两组间有显著差异。两组间发现了 9 种有区别的细菌分类群。我们使用属分类群建立了一个随机森林模型来预测 BK 多瘤病毒感染状态，其准确性最佳（80.71%），曲线下面积为 0.82。最佳模型中包含两个属，即和。
BK 多瘤病毒感染患者的肠道微生物群失调，病毒感染过程中/比值增加。9 种有区别的细菌分类群可能是 BK 多瘤病毒感染的潜在生物标志物。随机森林模型预测 BKV 感染状态的准确性为 80.71%，其中包括和。
