Related Experiment Video

Updated: Jun 7, 2026

Therapeutic Evaluation of Fecal Microbiota Transplantation in an Interleukin 10-Deficient Mouse Model
05:41

Therapeutic Evaluation of Fecal Microbiota Transplantation in an Interleukin 10-Deficient Mouse Model

Published on: April 6, 2022

An Integrated Dataset of Clinical and Microbial Profiles for Fecal Microbiota Transplantation

Sen Yan1, Le Wang2,3, Yue Xu2,3

  • 1Department of Clinical Laboratory, Shanghai Tenth People's Hospital, Tongji University School of Medicine, Shanghai, 200072, China.

Scientific Data
|June 5, 2026
PubMed

Insights

A new dataset, FMTdb, integrates microbiota data from functional gastrointestinal disorder (FGID) patients receiving fecal microbiota transplantation (FMT). This resource aids in discovering biomarkers and developing personalized FGID treatments.

Area of Science:

  • Microbiome research
  • Gastroenterology
  • Data science

Background:

  • Functional gastrointestinal disorders (FGIDs) are common and debilitating.
  • Microbiota-targeted therapies like fecal microbiota transplantation (FMT) show promise but lack large-scale data for mechanistic insights and personalized application.
  • Existing studies are limited in scope and sample size.

Purpose of the Study:

  • To establish FMTdb, a comprehensive, integrated dataset for FGID patients undergoing FMT.
  • To facilitate biomarker discovery and mechanistic exploration in FGIDs.
  • To support the development of personalized, microbiota-based interventions for FGIDs.

Main Methods:

  • Curated a dataset integrating demographic, clinical, and multi-omic microbiota data.
  • Included data from 15 screened long-term donors, 370 FGID recipients, and 2,008 healthy controls.
  • Collected longitudinal metadata on donor follow-up and recipient pre/post-treatment observations.

Main Results:

  • FMTdb provides a multi-layered dataset connecting microbial composition with host response.
  • The dataset enables robust analysis of microbiota alterations in FGID patients treated with FMT.
  • Facilitates identification of potential biomarkers and therapeutic targets.

Conclusions:

  • FMTdb serves as a valuable resource for advancing FGID research.
  • The integrated data supports the development of precision medicine approaches for FGIDs.
  • This platform is crucial for understanding FMT efficacy and optimizing microbiota-based therapies.

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