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. 2013 Jan 24;14(1):R4.
doi: 10.1186/gb-2013-14-1-r4.

Inflammation-associated enterotypes, host genotype, cage and inter-individual effects drive gut microbiota variation in common laboratory mice

Falk Hildebrand, Thi Loan Anh Nguyen, Brigitta Brinkman, Roberto Garcia Yunta, Benedicte Cauwe, Peter Vandenabeele, Adrian Liston, Jeroen Raes

Inflammation-associated enterotypes, host genotype, cage and inter-individual effects drive gut microbiota variation in common laboratory mice

Falk Hildebrand et al. Genome Biol. .

"VSports" Abstract

Background: Murine models are a crucial component of gut microbiome research VSports手机版. Unfortunately, a multitude of genetic backgrounds and experimental setups, together with inter-individual variation, complicates cross-study comparisons and a global understanding of the mouse microbiota landscape. Here, we investigate the variability of the healthy mouse microbiota of five common lab mouse strains using 16S rDNA pyrosequencing. .

Results: We find initial evidence for richness-driven, strain-independent murine enterotypes that show a striking resemblance to those in human, and which associate with calprotectin levels, a marker for intestinal inflammation V体育安卓版. After enterotype stratification, we find that genetic, caging and inter-individual variation contribute on average 19%, 31. 7% and 45. 5%, respectively, to the variance in the murine gut microbiota composition. Genetic distance correlates positively to microbiota distance, so that genetically similar strains have more similar microbiota than genetically distant ones. Specific mouse strains are enriched for specific operational taxonomic units and taxonomic groups, while the 'cage effect' can occur across mouse strain boundaries and is mainly driven by Helicobacter infections. .

Conclusions: The detection of enterotypes suggests a common ecological cause, possibly low-grade inflammation that might drive differences among gut microbiota composition in mammals. Furthermore, the observed environmental and genetic effects have important consequences for experimental design in mouse microbiome research V体育ios版. .

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"V体育安卓版" Figures

Figure 1
Figure 1
Enterotype clusters detected in the data. (a) Nonmetric multidimensional scaling (NMDS) at the genus level shows two clusters in the dataset. (b) The density of the first NMDS axis that explains most of the variation (92.5%) and shows a bimodal distribution with only few intermediate samples. (c) The operational taxonomic unit (OTU) richness estimate (chao1) between these two clusters differs substantially and (d) the two clusters are dominated by different taxa, with enterotype 2 being dominated by Bacteroidetes and Enterobacteriaceae and enterotype 1 being driven by Runinococcus and Lachnospiraceae. Significances are shown by asterisks: *q < 0.1 and P < 0.05; ** q < 0.05; ***q < 0.01.
Figure 2
Figure 2
Calprotectin concentration (ng/ml) in enterotype 1 (ET1) and enterotype 2 (ET2). An elevated concentration of calprotectin was found in Bacteroidetes dominant enterotype (ET2) (P = 4.9 × 10-5, Wilcox rank sum test).
Figure 3
Figure 3
NMDS plot of enteroype 1 stratified sample set at the phylum level. Samples are colored by mouse genotypes and the percent of variation explained by each axis is indicated in parentheses.
Figure 4
Figure 4
The genetic distance between mouse strains is significantly correlated to phylum level microbiota distances. A Procrustes superimposition of the NMDS of both data types shows a clear association between mouse genotypes and microbiota composition. The P-value is calculated separately with a Mantel test.
Figure 5
Figure 5
Taxa differences between genotypes and cages. (a) Several genera are significantly different in abundance between genotypes, with a cutoff of P < 0.05 and q < 0.1. (b) The significantly different OTUs between cages. On the y-axis log10 scaled rarefied 16S reads per sample are shown. OTU identifiers refer to the following taxonomic assignments: 106 = Helicobacter; 596, 216, 133 = Porphyromonadaceae; 241 = Sphingomonas.
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