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Related Experiment Video

Updated: Jul 12, 2026

Microbiota Analysis Using Two-step PCR and Next-generation 16S rRNA Gene Sequencing
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A novel robust network construction and analysis workflow for mining infant microbiota relationships.

Wei Jiang1, Yue Zhai1, Dongbo Chen1

  • 1Laboratory of Microbiology, Immunology, and Metabolism, Diprobio (Shanghai) Co., Limited, Shanghai, China.

Msystems
|January 2, 2025
PubMed
Summary

A new Probability-Based Co-Detection Model (PBCDM) reliably analyzes infant gut microbiota development. This method identifies core microbial relationships, revealing increasing competition as the infant microbiome matures.

Keywords:
co-existence networkinfant microbiotamicrobial networknetwork robustness

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Area of Science:

  • Microbiome research
  • Network analysis
  • Infant health

Background:

  • The infant gut microbiota is critical for health, with its development in the first 1,000 days impacting long-term outcomes.
  • Understanding microbial relationships is key to linking microbiota maturation to health.
  • Existing network methods for analyzing infant microbiota lack robust evaluation strategies.

Purpose of the Study:

  • To develop and validate a reliable network-based method for analyzing infant gut microbiota.
  • To assess the performance of different network construction and evaluation approaches.
  • To identify core microbial genera and their relationships during infant development.

Main Methods:

  • Created a test data pool from public infant microbiome datasets.
  • Evaluated four network-based methods using repeated sampling.
  • Developed and applied the Probability-Based Co-Detection Model (PBCDM).
  • Utilized a network shearing strategy based on percolation theory to identify core genera.

Main Results:

  • The PBCDM demonstrated superior stability and robustness in network attribute analysis.
  • PBCDM-constructed networks revealed microbial co-existence patterns in infants across different ages.
  • Identified core genera networks, showing increased similarity between adjacent age groups.
  • Observed a rise in competitive microbial relationships with infant microbiome maturation.

Conclusions:

  • The PBCDM provides a reliable approach for constructing and evaluating microbial co-existence networks.
  • PBCDM-based networks accurately reflect known infant microbiota features.
  • The methodology offers a promising tool for investigating microbial relationships and can be extended to other omics data.