Cell Host & Microbe
Volume 26, Issue 2, 14 August 2019, Pages 265-272.e4
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Short Article
Meta-Analysis Reveals Reproducible Gut Microbiome Alterations in Response to a High-Fat Diet

https://doi.org/10.1016/j.chom.2019.06.013Get rights and content
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Highlights

  • A generalizable approach is presented for meta-analysis of microbiome datasets

  • High-fat diets induce reproducible shifts in the mouse gut microbiome

  • Nonviable Lactococcus contamination is widespread in experimental diets

  • Phylogenetic and gene signatures translate to human microbiomes

Summary

Multiple research groups have shown that diet impacts the gut microbiome; however, variability in experimental design and quantitative assessment have made it challenging to assess the degree to which similar diets have reproducible effects across studies. Through an unbiased subject-level meta-analysis framework, we re-analyzed 27 dietary studies including 1,101 samples from rodents and humans. We demonstrate that a high-fat diet (HFD) reproducibly changes gut microbial community structure. Finer taxonomic analysis revealed that the most reproducible signals of a HFD are Lactococcus species, which we experimentally demonstrate to be common dietary contaminants. Additionally, a machine-learning approach defined a signature that predicts the dietary intake of mice and demonstrated that phylogenetic and gene-centric transformations of this model can be translated to humans. Together, these results demonstrate the utility of microbiome meta-analyses in identifying robust and reproducible features for mechanistic studies in preclinical models.

Keywords

microbiome
meta-analysis
high-fat diet
murine
machine learning
Lactococcus

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These authors contributed equally

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