Archaea and Fungi of the Human Gut Microbiome: Correlations with Diet and Bacterial Residents
Wu, Gary D.
Lewis, James D.
Bushman, Frederic D.
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CitationHoffmann, Christian, Serena Dollive, Stephanie Grunberg, Jun Chen, Hongzhe Li, Gary D. Wu, James D. Lewis, and Frederic D. Bushman. 2013. “Archaea and Fungi of the Human Gut Microbiome: Correlations with Diet and Bacterial Residents.” PLoS ONE 8 (6): e66019. doi:10.1371/journal.pone.0066019. http://dx.doi.org/10.1371/journal.pone.0066019.
AbstractDiet influences health as a source of nutrients and toxins, and by shaping the composition of resident microbial populations. Previous studies have begun to map out associations between diet and the bacteria and viruses of the human gut microbiome. Here we investigate associations of diet with fungal and archaeal populations, taking advantage of samples from 98 well-characterized individuals. Diet was quantified using inventories scoring both long-term and recent diet, and archaea and fungi were characterized by deep sequencing of marker genes in DNA purified from stool. For fungi, we found 66 genera, with generally mutually exclusive presence of either the phyla Ascomycota or Basiodiomycota. For archaea, Methanobrevibacter was the most prevalent genus, present in 30% of samples. Several other archaeal genera were detected in lower abundance and frequency. Myriad associations were detected for fungi and archaea with diet, with each other, and with bacterial lineages. Methanobrevibacter and Candida were positively associated with diets high in carbohydrates, but negatively with diets high in amino acids, protein, and fatty acids. A previous study emphasized that bacterial population structure was associated primarily with long-term diet, but high Candida abundance was most strongly associated with the recent consumption of carbohydrates. Methobrevibacter abundance was associated with both long term and recent consumption of carbohydrates. These results confirm earlier targeted studies and provide a host of new associations to consider in modeling the effects of diet on the gut microbiome and human health.
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