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. 2020 Mar;214(3):719-733.
doi: 10.1534/genetics.119.303013. Epub 2020 Jan 2.

A Microbe Associated With Sleep Revealed by a Novel Systems Genetic Analysis of the Microbiome in Collaborative Cross Mice

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Free PMC article

A Microbe Associated With Sleep Revealed by a Novel Systems Genetic Analysis of the Microbiome in Collaborative Cross Mice

Jason A Bubier et al. Genetics. .
Free PMC article

Abstract

The microbiome influences health and disease through complex networks of host genetics, genomics, microbes, and environment. Identifying the mechanisms of these interactions has remained challenging. Systems genetics in laboratory mice (Mus musculus) enables data-driven discovery of biological network components and mechanisms of host-microbial interactions underlying disease phenotypes. To examine the interplay among the whole host genome, transcriptome, and microbiome, we mapped QTL and correlated the abundance of cecal messenger RNA, luminal microflora, physiology, and behavior in a highly diverse Collaborative Cross breeding population. One such relationship, regulated by a variant on chromosome 7, was the association of Odoribacter (Bacteroidales) abundance and sleep phenotypes. In a test of this association in the BKS.Cg-Dock7m +/+ Leprdb/J mouse model of obesity and diabetes, known to have abnormal sleep and colonization by Odoribacter, treatment with antibiotics altered sleep in a genotype-dependent fashion. The many other relationships extracted from this study can be used to interrogate other diseases, microbes, and mechanisms.

Keywords: behavior; bioinformatics; genetics; genomics; sleep.

Figures

Figure 1
Figure 1
(A) The systems genetic model and gut microbiomics. Genetic variation in a host population together with the environment interact to affect intestinal gene expression in the host, microbial abundance, and disease-related traits in the host. There is significant bidirectional interplay among the microbiome, host gene expression, and disease-related phenotypes; however, the effect of host genotype is unidirectional, and therefore causal. (B) The analysis and decision steps used in this study of the relationship of the microbiome, cecal transcriptome, phenotype, and genotypes of Collaborative Cross mice, and then the analysis used in the validation experiment.
Figure 2
Figure 2
Odoribacter abundance in the cecum. (A) Genome scan showing a significant QTL (P < 0.01) peak on Chr 7. Horizontal lines represent permuted significance thresholds. From the top down: highly significant, P < 0.01; significant, P < 0.05; highly suggestive, P < 0.1; and suggestive, P < 0.63. (B) Detailed QTL map on chromosome 7. Bottom: LOD score across Chr 7. Top: allelic effect plots of eight coefficients of the QTL mixed model representing the effect of each CC founder haplotype on phenotype. The NZO allele on Chr 7 is associated with increased abundance of Odoribacter (C) Top: LOD score for SNP association mapping in the QTL support interval (67.1–71.1). Red points indicate SNPs with significant association to Odoribacter abundance. Bottom: genes and noncoding RNAs located in the QTL interval. (D) Ingenuity Pathway Analysis of the positional candidate genes together with Lepr show a network path through Vegf, and involving either Nr2f2 or Igf1r. (E) Inferred network relating sleep, microbe abundance, microbial abundance QTL, expression correlations, and mutant mice. The network is a consensus representation of the 40 most likely Bayesian networks in an MCMC sample. Edge weights correspond to the marginal frequency of each directed edge in the top 40 BNs. Sleep 1 represents the sleep trait corresponding to the average of continuous sleep lengths over 4 full days, and Sleep 2 represents the sleep trait activity onset on the fourth day (hr). CC, Collaborative Cross; Chr, chromosome; MCMC, Markov Chain Monte Carlo.
Figure 3
Figure 3
Mean and SE for the “% time sleep” over a 5-day test, with cyclic patterns characterized on the right by an FFT of the mean sleep percentage time series. (A) WT water only, (B) db/db mice water (C), WT given antibiotics, and (D) db/db mice given antibiotics. Genotype and antibiotic treatment have a significant interaction affecting “% Sleep” time. Night and day cycles shown with white and black bars, respectively. The FFT amplitudes of the regions of the % Sleep graphs in white are summarized in the graphs on the right. Percent sleep time for the antibiotic-treated db/db mice over a 72-hr period showed a genotype × treatment interaction in a repeated measure multivariate ANOVA; time × genotype × treatment F(71,45) = 2.1199, P = 0.0040 (Figure 3, A–D). Post hoc contrast analysis revealed significant (P < 0.001) differences between control db/db mice and all three other groups (P < 0.001). (E) FFT peak amplitudes for each mouse corresponding to sleep percentage cycles, with periods ranging from 4 to 7 hr (shown with the dotted lines) during the final 4 days of the sleep cycle, shows significant genotype × treatment interaction as well as the db/db control being significantly different from the other three groups. (F) Two of the microbes present in the control db/db mice, but absent in the db/db antibiotic-treated mice. FFT, fast Fourier transform; WT, wild-type.

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