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A Method to Assess Bacteriocin Effects on the Gut Microbiota of Mice

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Published on: July 25, 2017

Comprehensive microbiome causal mediation analysis using MiMed on user-friendly web interfaces.

Hyojung Jang¹, Solha Park¹, Hyunwook Koh¹

¹Department of Applied Mathematics and Statistics, The State University of New York, Korea, Incheon, South Korea.

Biology Methods & Protocols

|October 16, 2023

Summary

This summary is machine-generated.

A new platform, MiMed, simplifies microbiome mediation analysis for researchers. It automates data processing, analysis, and visualization, making complex microbiome-environment-health links more accessible.

Keywords:

causal inference causal mediation analysis human microbiome microbiome data analysis web cloud computing

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Area of Science:

Microbiome research
Computational biology
Statistical genetics

Background:

Human microbiome studies aim to link environmental exposures to health outcomes via microbial mediation.
Mediation analysis is underutilized in microbiome research due to a lack of user-friendly tools and researcher familiarity with complex methods.
Existing tools often require advanced programming skills, limiting accessibility for interdisciplinary researchers.

Purpose of the Study:

To introduce MiMed, a web cloud computing platform designed for comprehensive microbiome mediation analysis (MiMed).
To provide a user-friendly interface for microbiome data processing, diversity calculation, normalization, and downstream analysis.
To facilitate the investigation of microbial roles in mediating exposure-disease relationships.

Main Methods:

MiMed offers modules for analyzing microbial ecosystems (alpha/beta diversity) and individual taxa with various normalization methods.
Includes covariate-adjusted analysis to control for confounders like age and gender, enhancing causal inference.
Features statistical inference for mediation effect estimation and significance testing, alongside AI-powered literature search using ChatGPT for identified mediators.

Main Results:

MiMed successfully processed and analyzed microbiome data, demonstrating its utility in identifying mediating roles.
The platform facilitated covariate-adjusted analyses, strengthening the interpretation of mediation effects.
Demonstrated application in a study of oral microbiome mediation between e-cigarette smoking and gingival inflammation.

Conclusions:

MiMed provides a comprehensive, automated, and user-friendly solution for microbiome mediation analysis.
The platform democratizes access to advanced statistical methods for researchers across disciplines.
MiMed is expected to advance the understanding of the microbiome's role in mediating environmental exposures and health outcomes.