Cited by 402Gut microbiota and healthNutrition, Genetics, and DiseaseOral microbiology and periodontitis research

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Genetic and environmental control of host-gut microbiota interactions

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Abstract

Genetics provides a potentially powerful approach to dissect host-gut microbiota interactions. Toward this end, we profiled gut microbiota using 16s rRNA gene sequencing in a panel of 110 diverse inbred strains of mice. This panel has previously been studied for a wide range of metabolic traits and can be used for high-resolution association mapping. Using a SNP-based approach with a linear mixed model, we estimated the heritability of microbiota composition. We conclude that, in a controlled environment, the genetic background accounts for a substantial fraction of abundance of most common microbiota. The mice were previously studied for response to a high-fat, high-sucrose diet, and we hypothesized that the dietary response was determined in part by gut microbiota composition. We tested this using a cross-fostering strategy in which a strain showing a modest response, SWR, was seeded with microbiota from a strain showing a strong response, A×B19. Consistent with a role of microbiota in dietary response, the cross-fostered SWR pups exhibited a significantly increased response in weight gain. To examine specific microbiota contributing to the response, we identified various genera whose abundance correlated with dietary response. Among these, we chose Akkermansia muciniphila, a common anaerobe previously associated with metabolic effects. When administered to strain A×B19 by gavage, the dietary response was significantly blunted for obesity, plasma lipids, and insulin resistance. In an effort to further understand host-microbiota interactions, we mapped loci controlling microbiota composition and prioritized candidate genes. Our publicly available data provide a resource for future studies.

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Figure 1. Phylum-level variability of gut microbiota composition across 113 inbred strains of mice. (A) Columns represent the relative abundance of microbial phyla in 113 strains (327 male and 297 female). (B) Box plot of β diversity distances between microbial communities obtained when comparing mice within and between strains. The specific distance metric used is indicated on the axes. (***) P < 0.001 for Student's t-test with 1000 Monte Carlo simulations. See also Supplemental Table 2.
Figure 1. Phylum-level variability of gut microbiota composition across 113 inbred strains of mice. (A) Columns represent the relative abundance of microbial phyla in 113 strains (327 male and 297 female). (B) Box plot of β diversity distances between microbial communities obtained when comparing mice within and between strains. The specific distance metric used is indicated on the axes. (***) P < 0.001 for Student's t-test with 1000 Monte Carlo simulations. See also Supplemental Table 2.CC BY · PubMed Central
Figure 2. Cross-fostering influences dietary responsiveness. (A) Body fat increase in SWR and A×B19 strains during 8 wk of the HF/HS diet. (B) Principal Coordinate Analysis (PCoA) of unweighted UniFrac distances for fecal samples after cross-fostering newborn SWR and A×B19 pups between parents (blue = A×B19 mothers, red = SWR mothers, and green = cross-fostered SWR pups), P < 0.05 for unweighted UniFrac using Student's t-test with 1000 Monte Carlo simulations. (C) Body fat changes after cross-fostering SWR pups with A×B19 mother (CF-SWR) compared to SWR and A×B19 controls. (D) Total body fat percentage after 8 wk of HF/HS feeding. (E) Plasma triglycerides (TG) levels. (F) PCoA of unweighted UniFrac distances for cecum samples after 8 wk of the HF/HS diet (blue = A×B19, red = SWR, green = cross-fostered SWR). Significant differences: (*) P < 0.05, (****) P < 0.0001, according to unpaired two-tailed Student's t-test. See also Supplemental Figure 2.
Figure 2. Cross-fostering influences dietary responsiveness. (A) Body fat increase in SWR and A×B19 strains during 8 wk of the HF/HS diet. (B) Principal Coordinate Analysis (PCoA) of unweighted UniFrac distances for fecal samples after cross-fostering newborn SWR and A×B19 pups between parents (blue = A×B19 mothers, red = SWR mothers, and green = cross-fostered SWR pups), P < 0.05 for unweighted UniFrac using Student's t-test with 1000 Monte Carlo simulations. (C) Body fat changes after cross-fostering SWR pups with A×B19 mother (CF-SWR) compared to SWR and A×B19 controls. (D) Total body fat percentage after 8 wk of HF/HS feeding. (E) Plasma triglycerides (TG) levels. (F) PCoA of unweighted UniFrac distances for cecum samples after 8 wk of the HF/HS diet (blue = A×B19, red = SWR, green = cross-fostered SWR). Significant differences: (*) P < 0.05, (****) P < 0.0001, according to unpaired two-tailed Student's t-test. See also Supplemental Figure 2.CC BY · PubMed Central
Figure 3. Akkermansia muciniphila treatment reduces obesity and metabolic syndrome traits in mice fed a HF/HS diet. (A) Total body weight, body fat, mesenteric, retroperitoneal, gonadal, and subcutaneous fat depot weights (g per 100 g body weight) in mice treated by oral gavage with live or heat-inactivated A. muciniphila and fed a HF/HS diet (n = 5). (B) Glucose, insulin, HOMA-IR, unesterified cholesterol (UC), total cholesterol (TC), and triglycerides (TG) levels. (C) Relative abundance of bacterial genera between different treatment groups. Data are shown as means ± SD. Significant differences: (*) P < 0.05, (**) P < 0.01, (***) P < 0.001, (****) P < 0.0001, with unpaired two-tailed Student's t-test.
Figure 3. Akkermansia muciniphila treatment reduces obesity and metabolic syndrome traits in mice fed a HF/HS diet. (A) Total body weight, body fat, mesenteric, retroperitoneal, gonadal, and subcutaneous fat depot weights (g per 100 g body weight) in mice treated by oral gavage with live or heat-inactivated A. muciniphila and fed a HF/HS diet (n = 5). (B) Glucose, insulin, HOMA-IR, unesterified cholesterol (UC), total cholesterol (TC), and triglycerides (TG) levels. (C) Relative abundance of bacterial genera between different treatment groups. Data are shown as means ± SD. Significant differences: (*) P < 0.05, (**) P < 0.01, (***) P < 0.001, (****) P < 0.0001, with unpaired two-tailed Student's t-test.CC BY · PubMed Central
Figure 4. Genome-wide association mapping of gut microbiota genera in the HMDP: (A) Roseburia spp., (B) R. gnavus, (C) A. muciniphila, (D) Oscillospira spp., (E) Turicibacter spp. Association was performed using the FaST-LMM algorithm (Lippert et al. 2011) following correction for population structure using ∼200,000 filtered SNPs genotyped in all strains. The horizontal line indicates the threshold for genome-wide significance (P < 4 × 10−6). See also Supplemental Table 6.
Figure 4. Genome-wide association mapping of gut microbiota genera in the HMDP: (A) Roseburia spp., (B) R. gnavus, (C) A. muciniphila, (D) Oscillospira spp., (E) Turicibacter spp. Association was performed using the FaST-LMM algorithm (Lippert et al. 2011) following correction for population structure using ∼200,000 filtered SNPs genotyped in all strains. The horizontal line indicates the threshold for genome-wide significance (P < 4 × 10−6). See also Supplemental Table 6.CC BY · PubMed Central
Figure 5. Chromosome 15 locus for abundance of genus Roseburia spp. (A) Overlapping genome-wide significant associations with the abundance of Roseburia spp. and liver and adipose eQTLs of the Irak4 gene in HMDP mice fed a HF/HS diet. The horizontal line indicates the threshold for genome-wide significance (P < 4 × 10−6). (B,C) Correlations of Irak4 adipose gene expression with the relative abundance of Roseburia spp. and HOMA-IR in the HMDP mice. (r) Biweight midcorrelation, (p) P value. See also Supplemental Tables 6 and 7.
Figure 5. Chromosome 15 locus for abundance of genus Roseburia spp. (A) Overlapping genome-wide significant associations with the abundance of Roseburia spp. and liver and adipose eQTLs of the Irak4 gene in HMDP mice fed a HF/HS diet. The horizontal line indicates the threshold for genome-wide significance (P < 4 × 10−6). (B,C) Correlations of Irak4 adipose gene expression with the relative abundance of Roseburia spp. and HOMA-IR in the HMDP mice. (r) Biweight midcorrelation, (p) P value. See also Supplemental Tables 6 and 7.CC BY · PubMed Central
Figure 6. Chromosome 2 and 7 loci for abundance of A. muciniphila. (A) Locus plot for genome-wide significant association of A. muciniphila abundance to a Chromosome 7 locus, indicating the LD block (shaded in gray) and peak SNP rs33129247. Locations of candidate genes are indicated. (B) Locus plot for association with TG (triglyceride) at the Chromosome 7 locus. See also Supplemental Tables 6 and 7. (C) Chromosome 2 locus showing overlapping associations with the abundance of A. muciniphila and cis-eQTLs of the Ctnnbl1 and Lbp genes in adipose. (D) Correlation of epididymal adipose gene expression of Ctnnbl1 with body fat and insulin levels after 8 wk of the HF/HS diet. (E) Correlation of epididymal adipose gene expression of Lbp with body fat response and insulin levels after 8 wk of the HF/HS diet. (BF) Body fat, (r) biweight midcorrelation, (p) P value.
Figure 6. Chromosome 2 and 7 loci for abundance of A. muciniphila. (A) Locus plot for genome-wide significant association of A. muciniphila abundance to a Chromosome 7 locus, indicating the LD block (shaded in gray) and peak SNP rs33129247. Locations of candidate genes are indicated. (B) Locus plot for association with TG (triglyceride) at the Chromosome 7 locus. See also Supplemental Tables 6 and 7. (C) Chromosome 2 locus showing overlapping associations with the abundance of A. muciniphila and cis-eQTLs of the Ctnnbl1 and Lbp genes in adipose. (D) Correlation of epididymal adipose gene expression of Ctnnbl1 with body fat and insulin levels after 8 wk of the HF/HS diet. (E) Correlation of epididymal adipose gene expression of Lbp with body fat response and insulin levels after 8 wk of the HF/HS diet. (BF) Body fat, (r) biweight midcorrelation, (p) P value.CC BY · PubMed Central

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Metadata

Authors
Org, E., Parks, B. W., Joo, J. W. J., Emert, B., Schwartzman, W., Kang, E. Y., Mehrabian, M., Pan, C., Knight, R., Gunsalus, R., Drake, T. A., Eskin, E., & Lusis, A. J.
Affiliations
  • University of California, Los Angeles (US)
  • University of California San Diego (US)
Venue
Genome Research
Published
2015-08-10
Volume
25
Issue
10
Pages
1558-1569
ISSN
  • 1088-9051 (ISSN-L)
  • 1549-5469
OpenAlex
W2161377204
Cited by
381
References
70
Citations by year
2026: 8 · 2025: 16 · 2024: 28 · 2023: 34 · 2022: 36 · 2021: 75 · 2020: 41 · 2019: 27 · 2018: 38 · 2017: 36 · 2016: 38 · 2015: 3
Type
posted content
Language
en
Open access
Locations
  • Genome Research (publishedVersion)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • eScholarship (California Digital Library) (submittedVersion, cc-by)
Funders
  • National Institutes of Health (HL028481, HL30568, DK094311)
  • UCLA Iris Cantor Women's Health Center
  • MOBILITAS Postdoctoral Research (MJD252, 330381)
  • NIH (T32-HD07228)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gut microbiota and health
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Nutrition, Genetics, and Disease
  • Health Sciences › Dentistry › Periodontics › Oral microbiology and periodontitis research
Keywords
gut microbiota composition, inbred mouse strains, association mapping, cross-fostering, high-fat high-sugar diet, Akkermansia muciniphila, obesity, insulin resistance, plasma lipids, candidate genes
MeSH terms
Gastrointestinal Microbiome, Animals, Diet, Environment, Female, Male, Mice, Inbred Strains, Obesity, RNA, Ribosomal, 16S, Sucrose, Heredity, Mice, Genome-Wide Association Study, Diet, High-Fat

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