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Social network community structure and the contact-mediated sharing of commensal E. coli among captive rhesus macaques (Macaca mulatta)

Overview of attention for article published in PeerJ, January 2018
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (91st percentile)
  • High Attention Score compared to outputs of the same age and source (80th percentile)

Mentioned by

41 tweeters
1 Facebook page


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Readers on

36 Mendeley
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Social network community structure and the contact-mediated sharing of commensal E. coli among captive rhesus macaques (Macaca mulatta)
Published in
PeerJ, January 2018
DOI 10.7717/peerj.4271
Pubmed ID

Krishna Balasubramaniam, Brianne Beisner, Jiahui Guan, Jessica Vandeleest, Hsieh Fushing, Edward Atwill, Brenda McCowan


In group-living animals, heterogeneity in individuals' social connections may mediate the sharing of microbial infectious agents. In this regard, the genetic relatedness of individuals' commensal gut bacterium Escherichia coli may be ideal to assess the potential for pathogen transmission through animal social networks. Here we use microbial phylogenetics and population genetics approaches, as well as host social network reconstruction, to assess evidence for the contact-mediated sharing of E. coli among three groups of captively housed rhesus macaques (Macaca mulatta), at multiple organizational scales. For each group, behavioral data on grooming, huddling, and aggressive interactions collected for a six-week period were used to reconstruct social network communities via the Data Cloud Geometry (DCG) clustering algorithm. Further, an E. coli isolate was biochemically confirmed and genotypically fingerprinted from fecal swabs collected from each macaque. Population genetics approaches revealed that Group Membership, in comparison to intrinsic attributes like age, sex, and/or matriline membership of individuals, accounted for the highest proportion of variance in E. coli genotypic similarity. Social network approaches revealed that such sharing was evident at the community-level rather than the dyadic level. Specifically, although we found no links between dyadic E. coli similarity and social contact frequencies, similarity was significantly greater among macaques within the same social network communities compared to those across different communities. Moreover, tests for one of our study-groups confirmed that E. coli isolated from macaque rectal swabs were more genotypically similar to each other than they were to isolates from environmentally deposited feces. In summary, our results suggest that among frequently interacting, spatially constrained macaques with complex social relationships, microbial sharing via fecal-oral, social contact-mediated routes may depend on both individuals' direct connections and on secondary network pathways that define community structure. They lend support to the hypothesis that social network communities may act as bottlenecks to contain the spread of infectious agents, thereby encouraging disease control strategies to focus on multiple organizational scales. Future directions includeincreasing microbial sampling effort per individual to better-detect dyadic transmission events, and assessments of the co-evolutionary links between sociality, infectious agent risk, and host immune function.

Twitter Demographics

The data shown below were collected from the profiles of 41 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 36 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 36 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 9 25%
Student > Ph. D. Student 8 22%
Student > Master 5 14%
Student > Doctoral Student 3 8%
Professor 2 6%
Other 3 8%
Unknown 6 17%
Readers by discipline Count As %
Agricultural and Biological Sciences 14 39%
Veterinary Science and Veterinary Medicine 3 8%
Psychology 2 6%
Social Sciences 2 6%
Environmental Science 2 6%
Other 5 14%
Unknown 8 22%

Attention Score in Context

This research output has an Altmetric Attention Score of 24. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 03 April 2020.
All research outputs
of 15,398,963 outputs
Outputs from PeerJ
of 8,855 outputs
Outputs of similar age
of 363,725 outputs
Outputs of similar age from PeerJ
of 370 outputs
Altmetric has tracked 15,398,963 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,855 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 17.9. This one has done well, scoring higher than 87% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 363,725 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 91% of its contemporaries.
We're also able to compare this research output to 370 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 80% of its contemporaries.