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PM2RA: A Framework for Detecting and Quantifying Relationship Alterations in Microbial Community.

Zhi Liu1, Kai Mi2, Zhenjiang Zech Xu3

  • 1State Key Laboratory of Reproductive Medicine, Center of Global Health, Nanjing Medical University, Nanjing 211166, China; Department of Pathogen Biology-Microbiology Division, Key Laboratory of Pathogen Biology of Jiangsu Province, Nanjing Medical University, Nanjing 211166, China; Key Laboratory of Human Functional Genomics of Jiangsu Province, Nanjing Medical University, Nanjing 211166, China.

Genomics, Proteomics & Bioinformatics
|February 13, 2021
PubMed
Summary

This study introduces Profile Monitoring for Microbial Relationship Alteration (PM2RA), a new framework to detect and quantify changes in gut microbe interactions. PM2RA offers a more sensitive approach to understanding disease pathogenesis by analyzing microbial relationship alterations.

Keywords:
Human diseaseMicrobial communityMicrobial relationship alterationMicrobiomeNetworkProfile monitoring

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Area of Science:

  • Microbiome research
  • Computational biology
  • Disease pathogenesis

Background:

  • Gut microbiota dysbiosis is linked to human diseases.
  • Microbe abundance shifts alone do not fully explain disease mechanisms.
  • Quantifying relationship alterations (RAs) in the microbiome is crucial for understanding disease but lacks direct methods.

Purpose of the Study:

  • To develop and validate a novel analysis framework, Profile Monitoring for Microbial Relationship Alteration (PM2RA), for identifying and quantifying microbial RAs.
  • To assess PM2RA's performance against existing methods using synthetic and real-world data.
  • To apply PM2RA to identify microbes associated with various diseases.

Main Methods:

  • Development of the PM2RA analysis framework.
  • Performance evaluation using synthetic microbiome data.
  • Validation on real microbial datasets from multiple disease contexts.
  • Application of PM2RA to identify disease-associated microbes.

Main Results:

  • PM2RA demonstrated higher specificity and sensitivity compared to co-occurrence-based methods.
  • PM2RA proved robust in quantifying microbial RAs across diverse datasets and diseases.
  • The framework identified novel and known microbes implicated in multiple human diseases.

Conclusions:

  • PM2RA is an effective tool for quantifying microbial RAs, offering deeper insights into disease pathogenesis.
  • The identified microbes warrant further investigation for their roles in human diseases.
  • PM2RA is available as a web-based application for broader scientific use.