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Social networks predict gut microbiome composition in wild baboons.

Tung J, Barreiro LB, Burns MB, Grenier JC, Lynch J, Grieneisen LE, Altmann J, Alberts SC, Blekhman R, Archie EA - Elife (2015)

Bottom Line: Social relationships have profound effects on health in humans and other primates, but the mechanisms that explain this relationship are not well understood.Using shotgun metagenomic data from wild baboons, we found that social group membership and social network relationships predicted both the taxonomic structure of the gut microbiome and the structure of genes encoded by gut microbial species.Our results argue that social interactions are an important determinant of gut microbiome composition in natural animal populations-a relationship with important ramifications for understanding how social relationships influence health, as well as the evolution of group living.

View Article: PubMed Central - PubMed

Affiliation: Department of Evolutionary Anthropology, Duke University, Durham, United States.

ABSTRACT
Social relationships have profound effects on health in humans and other primates, but the mechanisms that explain this relationship are not well understood. Using shotgun metagenomic data from wild baboons, we found that social group membership and social network relationships predicted both the taxonomic structure of the gut microbiome and the structure of genes encoded by gut microbial species. Rates of interaction directly explained variation in the gut microbiome, even after controlling for diet, kinship, and shared environments. They therefore strongly implicate direct physical contact among social partners in the transmission of gut microbial species. We identified 51 socially structured taxa, which were significantly enriched for anaerobic and non-spore-forming lifestyles. Our results argue that social interactions are an important determinant of gut microbiome composition in natural animal populations-a relationship with important ramifications for understanding how social relationships influence health, as well as the evolution of group living.

No MeSH data available.


Related in: MedlinePlus

Enrichment of low p-values in the data vs an empirical : within group network analysis.To confirm that our modeling approach (Moran's I statistic within Viola's group) did not bias us towards detecting false positives, we compared the signal in our true data set against an empirically derived . The histogram distribution of p-values for the true data (gold) is plotted against the distribution of p-values from 10 permutations (blue). In each permutation, species abundance was scrambled across group members while keeping the modeling approach and social network structure constant. The inset shows a quantile–quantile plot of the same data, with clear enrichment of socially structured species in the actual data vs the empirical . No socially structured species are detected at a 10% FDR in the permuted data sets, while 51 are discovered in the true data set.DOI:http://dx.doi.org/10.7554/eLife.05224.013
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fig3s2: Enrichment of low p-values in the data vs an empirical : within group network analysis.To confirm that our modeling approach (Moran's I statistic within Viola's group) did not bias us towards detecting false positives, we compared the signal in our true data set against an empirically derived . The histogram distribution of p-values for the true data (gold) is plotted against the distribution of p-values from 10 permutations (blue). In each permutation, species abundance was scrambled across group members while keeping the modeling approach and social network structure constant. The inset shows a quantile–quantile plot of the same data, with clear enrichment of socially structured species in the actual data vs the empirical . No socially structured species are detected at a 10% FDR in the permuted data sets, while 51 are discovered in the true data set.DOI:http://dx.doi.org/10.7554/eLife.05224.013

Mentions: To identify socially structured bacterial taxa within baboon social groups, we utilized a test of spatial autocorrelation, Moran's I, as implemented in the function Moran.I in the R package ape (Paradis et al., 2004). This analysis tests whether individuals with closer social bonds (as measured by the pairwise matrix of grooming strengths) tend to have more similar values for taxon abundance than those with weak or absent social bonds. Here, we again investigated the 327 most prevalent species from the MetaPhlAn 2.0 analysis. For this analysis, our power was constrained by the number of individuals in the social group. Thus, while we identified a large number of socially structured species within Viola's group (n = 51 of 327 species tested, at a false discovery rate of 10%), we did not observe strong evidence for socially structured species within Mica's group. Further investigation suggests this result is a consequence of sample size, as subsampling Viola's group (n = 29 individuals) to the size of Mica's group (n = 19 individuals) also resulted in little power to detect socially structured species. More than half of the time (58% of 100 random subsamples), fewer than 5 such cases were detected in Viola's group after subsampling, and more than a third of the time (35%) no cases could be detected with the smaller sample size. Hence, we focused on results from Viola's group. We again used a 10% FDR threshold to identify significant taxa in this analysis, after ensuring that the empirical distribution was uniform (Figure 3—figure supplement 2).


Social networks predict gut microbiome composition in wild baboons.

Tung J, Barreiro LB, Burns MB, Grenier JC, Lynch J, Grieneisen LE, Altmann J, Alberts SC, Blekhman R, Archie EA - Elife (2015)

Enrichment of low p-values in the data vs an empirical : within group network analysis.To confirm that our modeling approach (Moran's I statistic within Viola's group) did not bias us towards detecting false positives, we compared the signal in our true data set against an empirically derived . The histogram distribution of p-values for the true data (gold) is plotted against the distribution of p-values from 10 permutations (blue). In each permutation, species abundance was scrambled across group members while keeping the modeling approach and social network structure constant. The inset shows a quantile–quantile plot of the same data, with clear enrichment of socially structured species in the actual data vs the empirical . No socially structured species are detected at a 10% FDR in the permuted data sets, while 51 are discovered in the true data set.DOI:http://dx.doi.org/10.7554/eLife.05224.013
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4379495&req=5

fig3s2: Enrichment of low p-values in the data vs an empirical : within group network analysis.To confirm that our modeling approach (Moran's I statistic within Viola's group) did not bias us towards detecting false positives, we compared the signal in our true data set against an empirically derived . The histogram distribution of p-values for the true data (gold) is plotted against the distribution of p-values from 10 permutations (blue). In each permutation, species abundance was scrambled across group members while keeping the modeling approach and social network structure constant. The inset shows a quantile–quantile plot of the same data, with clear enrichment of socially structured species in the actual data vs the empirical . No socially structured species are detected at a 10% FDR in the permuted data sets, while 51 are discovered in the true data set.DOI:http://dx.doi.org/10.7554/eLife.05224.013
Mentions: To identify socially structured bacterial taxa within baboon social groups, we utilized a test of spatial autocorrelation, Moran's I, as implemented in the function Moran.I in the R package ape (Paradis et al., 2004). This analysis tests whether individuals with closer social bonds (as measured by the pairwise matrix of grooming strengths) tend to have more similar values for taxon abundance than those with weak or absent social bonds. Here, we again investigated the 327 most prevalent species from the MetaPhlAn 2.0 analysis. For this analysis, our power was constrained by the number of individuals in the social group. Thus, while we identified a large number of socially structured species within Viola's group (n = 51 of 327 species tested, at a false discovery rate of 10%), we did not observe strong evidence for socially structured species within Mica's group. Further investigation suggests this result is a consequence of sample size, as subsampling Viola's group (n = 29 individuals) to the size of Mica's group (n = 19 individuals) also resulted in little power to detect socially structured species. More than half of the time (58% of 100 random subsamples), fewer than 5 such cases were detected in Viola's group after subsampling, and more than a third of the time (35%) no cases could be detected with the smaller sample size. Hence, we focused on results from Viola's group. We again used a 10% FDR threshold to identify significant taxa in this analysis, after ensuring that the empirical distribution was uniform (Figure 3—figure supplement 2).

Bottom Line: Social relationships have profound effects on health in humans and other primates, but the mechanisms that explain this relationship are not well understood.Using shotgun metagenomic data from wild baboons, we found that social group membership and social network relationships predicted both the taxonomic structure of the gut microbiome and the structure of genes encoded by gut microbial species.Our results argue that social interactions are an important determinant of gut microbiome composition in natural animal populations-a relationship with important ramifications for understanding how social relationships influence health, as well as the evolution of group living.

View Article: PubMed Central - PubMed

Affiliation: Department of Evolutionary Anthropology, Duke University, Durham, United States.

ABSTRACT
Social relationships have profound effects on health in humans and other primates, but the mechanisms that explain this relationship are not well understood. Using shotgun metagenomic data from wild baboons, we found that social group membership and social network relationships predicted both the taxonomic structure of the gut microbiome and the structure of genes encoded by gut microbial species. Rates of interaction directly explained variation in the gut microbiome, even after controlling for diet, kinship, and shared environments. They therefore strongly implicate direct physical contact among social partners in the transmission of gut microbial species. We identified 51 socially structured taxa, which were significantly enriched for anaerobic and non-spore-forming lifestyles. Our results argue that social interactions are an important determinant of gut microbiome composition in natural animal populations-a relationship with important ramifications for understanding how social relationships influence health, as well as the evolution of group living.

No MeSH data available.


Related in: MedlinePlus