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Forensic analysis of the microbiome of phones and shoes
BACKGROUND: Microbial interaction between human-associated objects and the environments we inhabit may have forensic implications, and the extent to which microbes are shared between individuals inhabiting the same space may be relevant to human health and disease transmission. In this study, two pa...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4427962/ https://www.ncbi.nlm.nih.gov/pubmed/25969737 http://dx.doi.org/10.1186/s40168-015-0082-9 |
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author | Lax, Simon Hampton-Marcell, Jarrad T Gibbons, Sean M Colares, Geórgia Barguil Smith, Daniel Eisen, Jonathan A Gilbert, Jack A |
author_facet | Lax, Simon Hampton-Marcell, Jarrad T Gibbons, Sean M Colares, Geórgia Barguil Smith, Daniel Eisen, Jonathan A Gilbert, Jack A |
author_sort | Lax, Simon |
collection | PubMed |
description | BACKGROUND: Microbial interaction between human-associated objects and the environments we inhabit may have forensic implications, and the extent to which microbes are shared between individuals inhabiting the same space may be relevant to human health and disease transmission. In this study, two participants sampled the front and back of their cell phones, four different locations on the soles of their shoes, and the floor beneath them every waking hour over a 2-day period. A further 89 participants took individual samples of their shoes and phones at three different scientific conferences. RESULTS: Samples taken from different surface types maintained significantly different microbial community structures. The impact of the floor microbial community on that of the shoe environments was strong and immediate, as evidenced by Procrustes analysis of shoe replicates and significant correlation between shoe and floor samples taken at the same time point. Supervised learning was highly effective at determining which participant had taken a given shoe or phone sample, and a Bayesian method was able to determine which participant had taken each shoe sample based entirely on its similarity to the floor samples. Both shoe and phone samples taken by conference participants clustered into distinct groups based on location, though much more so when an unweighted distance metric was used, suggesting sharing of low-abundance microbial taxa between individuals inhabiting the same space. CONCLUSIONS: Correlations between microbial community sources and sinks allow for inference of the interactions between humans and their environment. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s40168-015-0082-9) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-4427962 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-44279622015-05-13 Forensic analysis of the microbiome of phones and shoes Lax, Simon Hampton-Marcell, Jarrad T Gibbons, Sean M Colares, Geórgia Barguil Smith, Daniel Eisen, Jonathan A Gilbert, Jack A Microbiome Research BACKGROUND: Microbial interaction between human-associated objects and the environments we inhabit may have forensic implications, and the extent to which microbes are shared between individuals inhabiting the same space may be relevant to human health and disease transmission. In this study, two participants sampled the front and back of their cell phones, four different locations on the soles of their shoes, and the floor beneath them every waking hour over a 2-day period. A further 89 participants took individual samples of their shoes and phones at three different scientific conferences. RESULTS: Samples taken from different surface types maintained significantly different microbial community structures. The impact of the floor microbial community on that of the shoe environments was strong and immediate, as evidenced by Procrustes analysis of shoe replicates and significant correlation between shoe and floor samples taken at the same time point. Supervised learning was highly effective at determining which participant had taken a given shoe or phone sample, and a Bayesian method was able to determine which participant had taken each shoe sample based entirely on its similarity to the floor samples. Both shoe and phone samples taken by conference participants clustered into distinct groups based on location, though much more so when an unweighted distance metric was used, suggesting sharing of low-abundance microbial taxa between individuals inhabiting the same space. CONCLUSIONS: Correlations between microbial community sources and sinks allow for inference of the interactions between humans and their environment. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s40168-015-0082-9) contains supplementary material, which is available to authorized users. BioMed Central 2015-05-12 /pmc/articles/PMC4427962/ /pubmed/25969737 http://dx.doi.org/10.1186/s40168-015-0082-9 Text en © Lax et al.; licensee BioMed Central. 2015 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 work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Lax, Simon Hampton-Marcell, Jarrad T Gibbons, Sean M Colares, Geórgia Barguil Smith, Daniel Eisen, Jonathan A Gilbert, Jack A Forensic analysis of the microbiome of phones and shoes |
title | Forensic analysis of the microbiome of phones and shoes |
title_full | Forensic analysis of the microbiome of phones and shoes |
title_fullStr | Forensic analysis of the microbiome of phones and shoes |
title_full_unstemmed | Forensic analysis of the microbiome of phones and shoes |
title_short | Forensic analysis of the microbiome of phones and shoes |
title_sort | forensic analysis of the microbiome of phones and shoes |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4427962/ https://www.ncbi.nlm.nih.gov/pubmed/25969737 http://dx.doi.org/10.1186/s40168-015-0082-9 |
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