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Genotyping Oral Commensal Bacteria to Predict Social Contact and Structure
Social network structure is a fundamental determinant of human health, from infectious to chronic diseases. However, quantitative and unbiased approaches to measuring social network structure are lacking. We hypothesized that genetic relatedness of oral commensal bacteria could be used to infer soci...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5042546/ https://www.ncbi.nlm.nih.gov/pubmed/27684062 http://dx.doi.org/10.1371/journal.pone.0160201 |
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author | Francis, Stephen Starko Plucinski, Mateusz M. Wallace, Amelia D. Riley, Lee W. |
author_facet | Francis, Stephen Starko Plucinski, Mateusz M. Wallace, Amelia D. Riley, Lee W. |
author_sort | Francis, Stephen Starko |
collection | PubMed |
description | Social network structure is a fundamental determinant of human health, from infectious to chronic diseases. However, quantitative and unbiased approaches to measuring social network structure are lacking. We hypothesized that genetic relatedness of oral commensal bacteria could be used to infer social contact between humans, just as genetic relatedness of pathogens can be used to determine transmission chains of pathogens. We used a traditional, questionnaire survey-based method to characterize the contact network of the School of Public Health at a large research university. We then collected saliva from a subset of individuals to analyze their oral microflora using a modified deep sequencing multilocus sequence typing (MLST) procedure. We examined micro-evolutionary changes in the S. viridans group to uncover transmission patterns reflecting social network structure. We amplified seven housekeeping gene loci from the Streptococcus viridans group, a group of ubiquitous commensal bacteria, and sequenced the PCR products using next-generation sequencing. By comparing the generated S. viridans reads between pairs of individuals, we reconstructed the social network of the sampled individuals and compared it to the network derived from the questionnaire survey-based method. The genetic relatedness significantly (p-value < 0.001) correlated with social distance in the questionnaire-based network, and the reconstructed network closely matched the network derived from the questionnaire survey-based method. Oral commensal bacterial are thus likely transmitted through routine physical contact or shared environment. Their genetic relatedness can be used to represent a combination of social contact and shared physical space, therefore reconstructing networks of contact. This study provides the first step in developing a method to measure direct social contact based on commensal organism genotyping, potentially capable of unmasking hidden social networks that contribute to pathogen transmission. |
format | Online Article Text |
id | pubmed-5042546 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-50425462016-10-27 Genotyping Oral Commensal Bacteria to Predict Social Contact and Structure Francis, Stephen Starko Plucinski, Mateusz M. Wallace, Amelia D. Riley, Lee W. PLoS One Research Article Social network structure is a fundamental determinant of human health, from infectious to chronic diseases. However, quantitative and unbiased approaches to measuring social network structure are lacking. We hypothesized that genetic relatedness of oral commensal bacteria could be used to infer social contact between humans, just as genetic relatedness of pathogens can be used to determine transmission chains of pathogens. We used a traditional, questionnaire survey-based method to characterize the contact network of the School of Public Health at a large research university. We then collected saliva from a subset of individuals to analyze their oral microflora using a modified deep sequencing multilocus sequence typing (MLST) procedure. We examined micro-evolutionary changes in the S. viridans group to uncover transmission patterns reflecting social network structure. We amplified seven housekeeping gene loci from the Streptococcus viridans group, a group of ubiquitous commensal bacteria, and sequenced the PCR products using next-generation sequencing. By comparing the generated S. viridans reads between pairs of individuals, we reconstructed the social network of the sampled individuals and compared it to the network derived from the questionnaire survey-based method. The genetic relatedness significantly (p-value < 0.001) correlated with social distance in the questionnaire-based network, and the reconstructed network closely matched the network derived from the questionnaire survey-based method. Oral commensal bacterial are thus likely transmitted through routine physical contact or shared environment. Their genetic relatedness can be used to represent a combination of social contact and shared physical space, therefore reconstructing networks of contact. This study provides the first step in developing a method to measure direct social contact based on commensal organism genotyping, potentially capable of unmasking hidden social networks that contribute to pathogen transmission. Public Library of Science 2016-09-29 /pmc/articles/PMC5042546/ /pubmed/27684062 http://dx.doi.org/10.1371/journal.pone.0160201 Text en © 2016 Francis et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Francis, Stephen Starko Plucinski, Mateusz M. Wallace, Amelia D. Riley, Lee W. Genotyping Oral Commensal Bacteria to Predict Social Contact and Structure |
title | Genotyping Oral Commensal Bacteria to Predict Social Contact and Structure |
title_full | Genotyping Oral Commensal Bacteria to Predict Social Contact and Structure |
title_fullStr | Genotyping Oral Commensal Bacteria to Predict Social Contact and Structure |
title_full_unstemmed | Genotyping Oral Commensal Bacteria to Predict Social Contact and Structure |
title_short | Genotyping Oral Commensal Bacteria to Predict Social Contact and Structure |
title_sort | genotyping oral commensal bacteria to predict social contact and structure |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5042546/ https://www.ncbi.nlm.nih.gov/pubmed/27684062 http://dx.doi.org/10.1371/journal.pone.0160201 |
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