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. 2014 Nov 6;159(4):789-99.
doi: 10.1016/j.cell.2014.09.053.

Human genetics shape the gut microbiome

Julia K Goodrich  1 , Jillian L Waters  1 , Angela C Poole  1 , Jessica L Sutter  1 , Omry Koren  1 , Ran Blekhman  2 , Michelle Beaumont  3 , William Van Treuren  4 , Rob Knight  5 , Jordana T Bell  3 , Timothy D Spector  3 , Andrew G Clark  2 , Ruth E Ley  6
Affiliations

Human genetics shape the gut microbiome

Julia K Goodrich et al. Cell. .

Abstract

Host genetics and the gut microbiome can both influence metabolic phenotypes. However, whether host genetic variation shapes the gut microbiome and interacts with it to affect host phenotype is unclear. Here, we compared microbiotas across >1,000 fecal samples obtained from the TwinsUK population, including 416 twin pairs. We identified many microbial taxa whose abundances were influenced by host genetics. The most heritable taxon, the family Christensenellaceae, formed a co-occurrence network with other heritable Bacteria and with methanogenic Archaea. Furthermore, Christensenellaceae and its partners were enriched in individuals with low body mass index (BMI). An obese-associated microbiome was amended with Christensenella minuta, a cultured member of the Christensenellaceae, and transplanted to germ-free mice. C. minuta amendment reduced weight gain and altered the microbiome of recipient mice. Our findings indicate that host genetics influence the composition of the human gut microbiome and can do so in ways that impact host metabolism.

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Figures

Figure 1
Figure 1. Microbiomes are more similar for monozygotic than dizygotic twins
A, C-F: Box plots of beta-diversity distances between microbial communities obtained when comparing individuals within twinships for monozygotic (MZ) twin pairs and dizygotic (DZ) twin pairs, and between unrelated individuals (UN). A: the whole microbiome; C: the bacterial family Ruminococcaceae; D-E: the bacterial family Lachnospiraceae; F: the family Bacteroidaceae. The specific distance metric used in each analysis is indicated on the axes. *P<0.05, **P<0.01, ***P<0.001 for Student's t-tests with 1,000 Monte Carlo simulations. B: The average relative abundances in the whole dataset for the top six most prevalent bacterial families (unrarefied data, see Methods). Relates to Figure S1 and Table S1.
Figure 2
Figure 2. OTU relative abundances are more highly correlated within MZ than DZ twin pairs
At left is a phylogeny of taxa in the TwinsUK study (Greengenes tree pruned to include only OTUs shared by 50% of the TwinsUK participants) and at right are corresponding twin-pair intra class correlation coefficients (ICCs). ICCs were calculated for each OTU and the difference in correlation coefficients for MZ twin pairs versus DZ twin pairs. Bars pointing to the right indicate that the difference is positive (i.e., MZ ICCs > DZ ICCs) and bars pointing to the left indicate negative differences (DZ ICCs > MZ ICCs). The scale bar associated with the phylogeny shows substitutions/site. Relates to Figure S2.
Figure 3
Figure 3. Heritability of microbiota in the TwinsUK dataset
A: OTU Heritability (A from ACE model) estimates mapped onto a microbial phylogeny and displayed using a rainbow gradient from blue (A = 0) to red (A ≥ 0.4). This phylogenetic tree was obtained from the Greengenes database and pruned to include only nodes for which at least 50% of the TwinsUK participants were represented. B: The significance for the heritability values shown in A was determined using a permutation test (n=1,000) and are shown on the same phylogeny as in panel A. P values range from 0 (red) to >0.1 (blue). Relates to Figure S3 and Table S2.
Figure 4
Figure 4. MZ twin pairs have higher correlations of Christensenellaceae than DZ twin pairs in TwinsUK and Yatsunenko datasets
Scatter plots comparing the abundances of Christensenellaceae in the gut microbiota of MZ and DZ co-twins. Christensenellaceae abundances were transformed and adjusted to control for technical and other covariates (Residuals are plotted, see Supplemental Methods) and the data are separated by zygosity (MZ or DZ twins). A: TwinsUK dataset. B: Yatsunenko dataset.
Figure 5
Figure 5. Christensenellaceae is the hub of a consortium of co-occurring heritable microbes that are associated with a lean BMI
A and B show the same network built from SparCC correlation coefficients between sequence abundances collapsed at the family level. The nodes represent families and the edges represent the correlation coefficients between families. Edges are colored blue for a positive correlation and grey for a negative correlation, and the weight of the edge reflects the strength of the correlation. Nodes are positioned using an edge-weighted force directed layout. In panel A, the nodes are colored by the heritability of the family, and in panel B, the nodes are colored by the significance of the association families and a normal vs. obese BMI. Family names are either indicated on the panel, or nodes are given a letter code. Phylum Actinobacteria: (a) Actinomycetaceae, (b) Coriobacteriaceae; Phylum Bacteroidetes: (c) Barnesiellaceae, (d) Odoribacteraceae, (e) Paraprevotellaceae, (f) Porphyromonadaceae, (g) Prevotellaceae, (h) Rikenellaceae; Phylum Firmicutes: (i) Carnobacteriaceae, (j) Clostridiaceae, (k) Erysipelotrichaceae, (l) Eubacteriaceae, (m) Lachnospiraceae, (n) Lactobacillaceae, (o) Mogibacteriaceae, (p) Peptococcaceae, (q) Peptostreptococcaceae, (r) Ruminococcaceae, (s) Streptococcaceae, (t) Tissierellaceae, (u) Turicibacteraceae, (v) Unclassified Clostridiales, (w) Veillonellaceae; Phylum Proteobacteria: (x) Alcaligenaceae, (y) Enterobacteriaceae, (z) Oxalobacteraceae, (aa) Pasteurellaceae, (ab) Unclassified RF32; Phylum Verrucomicrobia: (ac) Verrucomicrobiaceae. Relates to Figure S4.
Figure 6
Figure 6. Fecal transplants from obese and lean UK Twins to germfree mice reveal levels of Christenenallaceae post-transfer mirror delayed weight gain
A: Median relative abundances for OTUs classified as the genus Christensenella in the four donor treatment groups over time in the recipient mouse microbiotas. B: Principal coordinates analysis of unweighted UniFrac distances for (i) the inoculum prior to transplantation, (ii) fecal samples at 4 time points, and (iii) cecal samples at Day 21 post-transplant; see panel legend for color key. The amount of variance described by the first two PCs is shown on the axes. C: Richness (Faith's PD) for the microbiomes of the transplant mice plotted against time (days post inoculation, with Day 0 = inoculation day). D: The mean values ± S.E.M. for PC3 derived for the same analysis as shown in panel B are plotted against time (Day 0 = inoculation day) for the four treatment groups. The amount of variance explained by PC3 is in parentheses. E: Percent weight change since inoculation for germfree mouse recipients of 21 donor stools that were obtained from lean or obese donors with or without detectable M. smithii, which was used as a marker for the Christensenellaceae consortium. Means for each treatment group are plotted ± S. E. M. F: Box plots for percent weight changes for the 4 groups at Day 12 post-transplant, when maximal weight differences were observed. Letters next to boxes indicate significant differences if letters are different (p < 0.05). For all panels, Dark blue = L+, lean donor with methanogens; Light blue = L-, lean donor lacking methanogens; Dark orange = O+, obese donor with methanogens; Light orange = O-, obese donor without methanogens. We repeated this experiment with a set of 21 new mice and unique human donors and recovered the same effect. Relates to Figure S5.
Figure 7
Figure 7. Addition of Christensenella minuta to donor stool leads to reduced weight and adiposity gains in recipient mice
A: Box plot of percent weight change for germfree mouse recipients of a single donor stool only (lacking detectable Christensenella in unrarefied 16S rRNA data) or the donor stool amended with live C. minuta. B: Box plots showing percent body fat for mice in each group at Day 21 N = 12 mice per treatment. C, D: Principal coordinates analysis of unweighted UniFrac distances for (i) the inoculum prior to transplantation, (ii) fecal samples at 5 time points post-transplant; see panel legend for color key. The amount of variance described by the first two PCs is shown on the axes. The same data projection is shown in panels C and D; sample symbols are colored by time point (C) and by treatment (D). E: Relationship between PCs from the PCoA analysis and levels of Oscillospira at Day 21 (rho = −0.71, P = P < 0.001). Symbols are colored by treatment. Relates to Figure S6.
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References

    1. Armougom F, Henry M, Vialettes B, Raccah D, Raoult D. Monitoring bacterial community of human gut microbiota reveals an increase in Lactobacillus in obese patients and Methanogens in anorexic patients. PLoS ONE. 2009;4:e7125. - PMC - PubMed
    1. Basseri RJ, Basseri B, Pimentel M, Chong K, Youdim A, Low K, Hwang L, Soffer E, Chang C, Mathur R. Intestinal methane production in obese individuals is associated with a higher body mass index. Gastr Hepatol. 2012;8:22–28. - PMC - PubMed
    1. Benson AK, Kelly SA, Legge R, Ma F, Low SJ, Kim J, Zhang M, Oh PL, Nehrenberg D, Hua K, et al. Individuality in gut microbiota composition is a complex polygenic trait shaped by multiple environmental and host genetic factors. Proc Natl Acad Sci U S A. 2010;107:18933–18938. - PMC - PubMed
    1. Bevins CL, Salzman NH. The potter's wheel: the host's role in sculpting its microbiota. Cell Mol Life Sci. 2011;68:3675–3685. - PMC - PubMed
    1. Bloemen JG, Venema K, van de Poll MC, Olde Damink SW, Buurman WA, Dejong CH. Short chain fatty acids exchange across the gut and liver in humans measured at surgery. Clin Nutr. 2009;28:657–661. - PubMed

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