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. 2008 Aug 26;3(8):e3064.
doi: 10.1371/journal.pone.0003064.

Predominant role of host genetics in controlling the composition of gut microbiota

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Predominant role of host genetics in controlling the composition of gut microbiota

Zaruhi A Khachatryan et al. PLoS One. .

Abstract

Background: The human gastrointestinal tract is inhabited by a very diverse symbiotic microbiota, the composition of which depends on host genetics and the environment. Several studies suggested that the host genetics may influence the composition of gut microbiota but no genes involved in host control were proposed. We investigated the effects of the wild type and mutated alleles of the gene, which encodes the protein called pyrin, one of the regulators of innate immunity, on the composition of gut commensal bacteria. Mutations in MEFV lead to the autoinflammatory disorder, familial Mediterranean fever (FMF, MIM249100), which is characterized by recurrent self-resolving attacks of fever and polyserositis, with no clinical signs of disease in remission.

Methodology/principal findings: A total of 19 FMF patients and eight healthy individuals were genotyped for mutations in the MEFV gene and gut bacterial diversity was assessed by sequencing 16S rRNA gene libraries and FISH analysis. These analyses demonstrated significant changes in bacterial community structure in FMF characterized by depletion of total numbers of bacteria, loss of diversity, and major shifts in bacterial populations within the Bacteroidetes, Firmicutes and Proteobacteria phyla in attack. In remission with no clinical signs of disease, bacterial diversity values were comparable with control but still, the bacterial composition was substantially deviant from the norm. Discriminant function analyses of gut bacterial diversity revealed highly specific, well-separated and distinct grouping, which depended on the allele carrier status of the host.

Conclusions/significance: This is the first report that clearly establishes the link between the host genotype and the corresponding shifts in the gut microbiota (the latter confirmed by two independent techniques). It suggests that the host genetics is a key factor in host-microbe interaction determining a specific profile of commensal microbiota in the human gut.

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Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Figure 1
Figure 1. Rarefaction curves obtained for clone libraries from healthy controls and FMF patients.
The rarefaction curves were generated by plotting the number of phylotypes (defined at 99% level) against the number of clones sequenced. The shape of the curves of observed phylotype richness indicates a trend of diminishing chance of finding new phylotypes as the sampling continues. Data for library in attack were extrapolated by empiric regression function a×x2b×exp(−c×x). Coefficient of regression determination (R2) was 99.9%. Regression statistics: adjusted R2 – 0.9991; standard error – 0.1720; a = 1.8690; b = 0.7104; c = 8.0466E-04. Healthy controls are shown in dark blue; FMF patients in remission – in red and attack – in green, the extrapolated curve is shown in light blue.
Figure 2
Figure 2. Collector's curves of the observed and estimated phylotype richness of 16S libraries.
Collector's curves of the observed (shown in dark blue) and estimated (Chao1 (light blue) and ACE (red)) phylotype richness calculated for healthy subjects (A), FMF remission (B), and FMF attack (C) with the phylogenetic depth defined at 99% level.
Figure 3
Figure 3. Comparison of the main bacterial groups identified by FISH between healthy and diseased groups.
Comparative analysis of relative proportions of bacterial groups detected by different oligonucleotide probes in fecal samples between FMF patients in remission and attack periods and healthy control group (by Kruskal-Wallis test for multiple comparisons). On box-and-whisker plots the points within boxes indicate the mean values of bacterial proportions, the boxes represent standard errors (SE) and the vertical bars represent standard deviations (SD).
Figure 4
Figure 4. Discriminant function analysis of FISH data.
Number of variables in model: 10; grouping - 3 groups. Wilks's lambda coefficient – 0.045; F-test - (20,16) = 2.95, p<0.016. Root 1, 2 – discriminant functions 1 and 2 (1st and 2nd canonical roots). Regions of group distribution are outlined by ellipses; healthy is shown in blue triangles, remission – in red circles, and attack – in green squares.

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