Cohabiting family members share microbiota with one another and with their dogs - PubMed (original) (raw)

Comparative Study

doi: 10.7554/eLife.00458.

Christian Lauber, Elizabeth K Costello, Catherine A Lozupone, Gregory Humphrey, Donna Berg-Lyons, J Gregory Caporaso, Dan Knights, Jose C Clemente, Sara Nakielny, Jeffrey I Gordon, Noah Fierer, Rob Knight

Affiliations

Comparative Study

Cohabiting family members share microbiota with one another and with their dogs

Se Jin Song et al. Elife. 2013.

Abstract

Human-associated microbial communities vary across individuals: possible contributing factors include (genetic) relatedness, diet, and age. However, our surroundings, including individuals with whom we interact, also likely shape our microbial communities. To quantify this microbial exchange, we surveyed fecal, oral, and skin microbiota from 60 families (spousal units with children, dogs, both, or neither). Household members, particularly couples, shared more of their microbiota than individuals from different households, with stronger effects of co-habitation on skin than oral or fecal microbiota. Dog ownership significantly increased the shared skin microbiota in cohabiting adults, and dog-owning adults shared more 'skin' microbiota with their own dogs than with other dogs. Although the degree to which these shared microbes have a true niche on the human body, vs transient detection after direct contact, is unknown, these results suggest that direct and frequent contact with our cohabitants may significantly shape the composition of our microbial communities. DOI:http://dx.doi.org/10.7554/eLife.00458.001.

Keywords: Human; companion animals; environmental microbial reservoirs; family structure; metagenomics; microbial community transmission.

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Conflict of interest statement

The authors declare that no competing interests exist.

Figures

Figure 1.

Figure 1.. Community similarity within and between families across body sites, and taxa contributing to these differences.

Panels (AD) show average unweighted UniFrac distances between family members (blue) and between members of different families (red). ‘Child’ refers to all offspring aged 3–18 years who cohabit with the parents. ‘Infants’ were considered to be individuals aged 0–12 months. Palm/Paw refers to the right palm in the human comparisons and the back left paw in the dog comparison. Although there are distinguishable differences between the left and right palm communities within and across individuals (Fierer et al., 2008), the same analysis using the left palms showed a similar pattern (Table 2) and neither composition nor diversity were different enough between palms or among the four dog paws to affect the overall patterns. Mean ± 95% CI and R values (ANOSIM) are shown. *p<0.05 and **p<0.001 based on 10,000 permutations. Panel (E) shows the families of bacteria that exhibit the greatest differences in the number of phylotypes (OTUs) shared within and between adult partners on the right palm. Bars represent the average number of shared phylotypes for a given bacterial family within partners from the same family (blue) and between partners of different families (red). Mean ± 95% CI shown. *p<0.05 after Bonferroni correction (Wilcoxon test). DOI:

http://dx.doi.org/10.7554/eLife.00458.006

Figure 2.

Figure 2.. Approach towards or departure from the ‘adult’ state in each body site with age.

(A) Each point represents the average distance (unweighted UniFrac in red; weighted UniFrac in blue) between each participant and all other participants in the ‘adult’ age bracket. Here we define baseline ‘adult’ as 30–45 years in age (the results are not sensitive to this threshold). R2 values (linear regression model) are shown. *p<0.01, **p<0.001. (B) Phylogenetic diversity (PD) of the communities on each body site is plotted for all of the offspring in the study (aged 0–18 years). DOI:

http://dx.doi.org/10.7554/eLife.00458.008

Figure 3.

Figure 3.. Community similarity and phylotype sharing between dogs-owners and their dogs.

The left panel shows the average unweighted UniFrac distance between adult dog-owners and their dogs (blue), between dog-owners and other (not their own) dogs (red), and between adults who do not own dogs and dogs (green). The right panel shows the number of phylotypes shared for the same categories. Comparisons are labeled on the y-axis such that the first body site listed corresponds to the dog and the second site corresponds to the human. Mean ± 95% CI shown. The presence of asterisks lacking brackets indicates that all pairwise comparisons within that group are significant. Generally, dog-owners tend to share more similar communities and more phylotypes with their own dogs than with other dogs. *p<0.05, **p<0.001 after Bonferroni correction (Wilcoxon test). DOI:

http://dx.doi.org/10.7554/eLife.00458.011

Figure 4.

Figure 4.. Alpha diversity and shared phylotypes in couples with and without dogs and children.

The left panels show rarefaction curves for skin communities of couples (including seniors) who have dogs (top, in red), those without dogs (top, in blue), couples (excluding seniors) with infants/children (bottom, in red), and those without infants/children (bottom, in blue). Mean ± 95% CI shown. The right panels show the average number of phylotypes shared among individuals from the same categories shown in the left panels. Mean ± 95% CI shown. *p<0.05, **p<0.001 after Bonferroni correction (Wilcoxon test). DOI:

http://dx.doi.org/10.7554/eLife.00458.012

Figure 5.

Figure 5.. Variation within and between the communities of skin, oral, and fecal samples from humans and dogs.

Panel (A) shows a PCoA plot of all the body habitats, using unweighted UniFrac distances of human and dog samples, rarefied at 5000 sequences/sample. Panels (BD) show select body habitats from the full plot. Panel (E) shows a summary of the taxa shaded by relative abundance at the phylum level broken down by specific body habitat; the seven most abundant taxa are shown in the legend. DOI:

http://dx.doi.org/10.7554/eLife.00458.016

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References

    1. Anderson M, Gorley R, Clarke K. 2008. PERMANOVA+ for PRIMER: guide to software and statistical methods. PRIMER-E, Plymouth, UK
    1. Bates D, Maechler M, Dai B. 2008. The lme4 package. http://lme4.r-forge.r-project.org/
    1. Benezra A, DeStefano J, Gordon JI. 2012. Anthropology of microbes. Proc Natl Acad Sci USA 109:6378–81. 10.1073/pnas.1200515109 - DOI - PMC - PubMed
    1. Caporaso JG, Kuczynski J, Stombaugh J, Bittinger K, Bushman FD, Costello EK, et al. 2010. QIIME allows analysis of high-throughput community sequencing data. Nat Meth 7:335–6. 10.1038/nmeth.f.303 - DOI - PMC - PubMed
    1. Caporaso JG, Lauber CL, Costello EK, Berg-Lyons D, Gonzalez A, Stombaugh J, et al. 2011. Moving pictures of the human microbiome. Genome Biol 12:R50. 10.1186/gb-2011-12-5-r50 - DOI - PMC - PubMed

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