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Biological and technical variability in mouse microbiota analysis and implications for sample size determination.

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Understanding gut microbiota (GM) variation in mice is crucial for research. This study quantifies biological and technical variability in GM, offering guidance for experimental design and highlighting the trade-offs between sample size and sequencing costs.

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Area of Science:

  • Microbiology
  • Animal Research
  • Bioinformatics

Background:

  • The gut microbiota (GM) significantly influences host phenotypes, making it a key area of biomedical research.
  • Environmental and biological factors introduce variability into mouse GM composition, potentially affecting study outcomes.
  • Standardized fecal sample collection is essential for reliable GM research in laboratory mice.

Purpose of the Study:

  • To quantify the effect size of biological and technical variation in mouse gut microbiota studies.
  • To provide practical guidance for designing microbiome studies involving laboratory mice.
  • To evaluate the impact of repeated fecal sampling on statistical power and experimental costs.

Main Methods:

  • Employed a hierarchical fecal sampling strategy, analyzing multiple samples from multiple mice.
  • Quantified variability in alpha- and beta-diversity metrics at technical and biological levels.
  • Simulated the effect of sequencing multiple fecal samples per mouse on effect size in a two-group experimental design.

Main Results:

  • Biological and technical variation contribute significant, yet smaller (3-30x lower), variability compared to experimental variables in high-intergroup variability settings.
  • Sequencing five fecal samples per mouse increased effect size, reducing animal numbers by 5% but significantly increasing sequencing costs.
  • Biological and technical factors can appreciably affect experimental paradigms with low mean differences.

Conclusions:

  • While repeated fecal sampling can enhance statistical power in mouse microbiome studies, the associated increase in sequencing costs may render it impractical.
  • Understanding and quantifying sources of variation is critical for robust experimental design in gut microbiota research.
  • Researchers must balance the need for statistical power with the practical constraints of sequencing costs when determining sample collection strategies.