ABSTRACT

Fecal microbiota transplantation (FMT) is a promising treatment for microbiota dysbiosis associated diseases, such as Clostridioides difficile infection (CDI) and inflammatory bowel disease (IBD). The engraftment of donor bacteria is essential for the effectiveness of FMT, which to some extent depends on the matching of donors and recipients. However, how different types of donor-derived bacteria affect FMT efficacy has not been fully dissected. We recruited two longitudinal IBD cohorts of 103 FMT recipients and further analyzed 1,280 microbiota datasets from 14 public CDI and IBD studies to uncover the effect of donor-derived microbiota in recipients. We found that two enterotypes, RCPT/E and RCPT/B (dominated by Enterobacteriaceae and Bacteroides, respectively), consistently exist in both CDI and IBD patients. Based on a time-course-based multi-cohort analysis of FMT fecal samples, we observed the interplay between recipient and donor-derived microbiota during FMT, in which the FMT outcome was significantly associated with the enterotype and microbiota distance between donor and recipient after FMT. We proposed a new measurement, the ratio of colonizers to residents after FMT (C2R), to quantify the engraftment of donor-derived bacteria in the recipients, and then constructed an enterotype-based statistical model for donor-recipient matching, which was validated by both cross-validation and an additional IBD FMT cohort (n = 42). We believe that with the accumulation of FMT multi-omics datasets, machine learning-based methods will be helpful for rational donor selection for improving efficacy and precision FMT practices.

 抽象的

粪便微生物群移植（FMT）是治疗微生物群失调相关疾病的一种有前景的方法，例如艰难梭菌感染（CDI）和炎症性肠病（IBD）。供体细菌的植入对于FMT的有效性至关重要，这在一定程度上取决于供体和受体的匹配。然而，不同类型的供体来源细菌如何影响 FMT 功效尚未得到充分剖析。我们招募了两个由 103 名 FMT 接受者组成的纵向 IBD 队列，并进一步分析了来自 14 项公共 CDI 和 IBD 研究的 1,280 个微生物群数据集，以揭示捐赠者来源的微生物群对接受者的影响。我们发现两种肠型，RCPT/E 和 RCPT/B（分别以肠杆菌科和拟杆菌为主）在 CDI 和 IBD 患者中一致存在。基于对 FMT 粪便样本的基于时间进程的多队列分析，我们观察了 FMT 期间受者和供者来源的微生物群之间的相互作用，其中 FMT 结果与供者和受者之间的肠型和微生物群距离显着相关。 FMMT。我们提出了一种新的测量方法，即 FMT 后定植者与居民的比率（C2R），以量化供者来源的细菌在受者体内的植入情况，然后构建了基于肠型的供者-受者匹配统计模型，并通过以下方法进行了验证：交叉验证和额外的 IBD FMT 队列 (n = 42)。我们相信，随着FMT多组学数据集的积累，基于机器学习的方法将有助于合理选择供者，以提高FMT实践的有效性和精准度。