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Antibiotics reduce genetic diversity of core species in the honeybee gut microbiome.

Kasie RaymannLouis-Marie BobayNancy A Moran
Published in: Molecular ecology (2017)
The gut microbiome plays a key role in animal health, and perturbing it can have detrimental effects. One major source of perturbation to microbiomes, in humans and human-associated animals, is exposure to antibiotics. Most studies of how antibiotics affect the microbiome have used amplicon sequencing of highly conserved 16S rRNA sequences, as in a recent study showing that antibiotic treatment severely alters the species-level composition of the honeybee gut microbiome. But because the standard 16S rRNA-based methods cannot resolve closely related strains, strain-level changes could not be evaluated. To address this gap, we used amplicon sequencing of protein-coding genes to assess effects of antibiotics on fine-scale genetic diversity of the honeybee gut microbiota. We followed the population dynamics of alleles within two dominant core species of the bee gut community, Gilliamella apicola and Snodgrassella alvi, following antibiotic perturbation. Whereas we observed a large reduction in genetic diversity in G. apicola, S. alvi diversity was mostly unaffected. The reduction in G. apicola diversity accompanied an increase in the frequency of several alleles, suggesting resistance to antibiotic treatment. We find that antibiotic perturbation can cause major shifts in diversity and that the extent of these shifts can vary substantially across species. Thus, antibiotics impact not only species composition, but also allelic diversity within species, potentially affecting hosts if variants with particular functions are reduced or eliminated. Overall, we show that amplicon sequencing of protein-coding genes, without clustering into operational taxonomic units, provides an accurate picture of the fine-scale dynamics of microbial communities over time.
Keyphrases
  • genetic diversity
  • single cell
  • healthcare
  • escherichia coli
  • genome wide
  • endothelial cells
  • small molecule
  • copy number
  • risk assessment
  • bioinformatics analysis