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Similarities and differences in gut microbiome composition correlate with dietary patterns of Indian and Chinese adults.

Abhishek JainXin Hui LiWei Ning Chen
Published in: AMB Express (2018)
The interaction between diet and gut microbiota, and ultimately their link to health, has turned into the concentration of huge research. However, this relationship still needs to be fully characterized, particularly in case of the Asian population. We compared the fecal bacterial diversity and composition of healthy Indian and Chinese adults, ages 22-35 years, using next-generation sequencing analysis on IlluminaHiSeq 2500 platform. Our analysis revealed unique community structure, dominant Firmicutes, Actinobacteria and underrepresented Bacteroides, of Indian and Chinese gut bacteria. This community structure closely matched with the gut bacterial composition of the Russian population. Therefore, we hypothesized that enrichment of these bacterial clades is supported by high consumption of starch-rich diet such as rice, potato, refined grains. The dominance of genus Bifidobacterium due to carbohydrate-rich diet is another notable feature of this study. Moreover, Indian gut bacteria are significantly represented by Bacteroidetes (p = 0.001) and Prevotella (p = 0.002) in contrast to Chinese, which could be associated with whole grains and plant-based vegetarian diet of Indians. The gut bacterial population of Indian adults were as diverse as Chinese adults (p > 0.1), but significant difference was noticed in gut bacterial composition and relative abundance between two populations (R = 0.625, p < 0.005). Partial least squares discriminant analysis and non-metric multidimensional scaling plots showed dietary habit wise clustering of subjects. Thus, the present work confirms an important role of diet in determining gut bacterial composition. LEfse analysis revealed genera Prevotella, Megasphaera, Catenibacterium, Lactobacillus, Ruminococcus and species Prevotella copri, Lactobacillus ruminis as the potential biomarkers of diet.
Keyphrases
  • physical activity
  • weight loss
  • healthcare
  • magnetic resonance
  • mental health
  • public health
  • machine learning
  • magnetic resonance imaging
  • risk assessment
  • rna seq
  • health information