Deep sequencing identifies ethnicity-specific bacterial signatures in the oral microbiome.

Oral infections have a strong ethnic predilection; suggesting that ethnicity is a critical determinant of oral microbial colonization. Dental plaque and saliva samples from 192 subjects belonging to four major ethnicities in the United States were analyzed using terminal restriction fragment length...

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Main Authors: Matthew R Mason, Haikady N Nagaraja, Terry Camerlengo, Vinayak Joshi, Purnima S Kumar
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2013-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC3806732?pdf=render
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spelling doaj-14650ed6e4d5429d8815b9eb40f9587e2020-11-25T01:02:46ZengPublic Library of Science (PLoS)PLoS ONE1932-62032013-01-01810e7728710.1371/journal.pone.0077287Deep sequencing identifies ethnicity-specific bacterial signatures in the oral microbiome.Matthew R MasonHaikady N NagarajaTerry CamerlengoVinayak JoshiPurnima S KumarOral infections have a strong ethnic predilection; suggesting that ethnicity is a critical determinant of oral microbial colonization. Dental plaque and saliva samples from 192 subjects belonging to four major ethnicities in the United States were analyzed using terminal restriction fragment length polymorphism (t-RFLP) and 16S pyrosequencing. Ethnicity-specific clustering of microbial communities was apparent in saliva and subgingival biofilms, and a machine-learning classifier was capable of identifying an individual's ethnicity from subgingival microbial signatures. The classifier identified African Americans with a 100% sensitivity and 74% specificity and Caucasians with a 50% sensitivity and 91% specificity. The data demonstrates a significant association between ethnic affiliation and the composition of the oral microbiome; to the extent that these microbial signatures appear to be capable of discriminating between ethnicities.http://europepmc.org/articles/PMC3806732?pdf=render
collection DOAJ
language English
format Article
sources DOAJ
author Matthew R Mason
Haikady N Nagaraja
Terry Camerlengo
Vinayak Joshi
Purnima S Kumar
spellingShingle Matthew R Mason
Haikady N Nagaraja
Terry Camerlengo
Vinayak Joshi
Purnima S Kumar
Deep sequencing identifies ethnicity-specific bacterial signatures in the oral microbiome.
PLoS ONE
author_facet Matthew R Mason
Haikady N Nagaraja
Terry Camerlengo
Vinayak Joshi
Purnima S Kumar
author_sort Matthew R Mason
title Deep sequencing identifies ethnicity-specific bacterial signatures in the oral microbiome.
title_short Deep sequencing identifies ethnicity-specific bacterial signatures in the oral microbiome.
title_full Deep sequencing identifies ethnicity-specific bacterial signatures in the oral microbiome.
title_fullStr Deep sequencing identifies ethnicity-specific bacterial signatures in the oral microbiome.
title_full_unstemmed Deep sequencing identifies ethnicity-specific bacterial signatures in the oral microbiome.
title_sort deep sequencing identifies ethnicity-specific bacterial signatures in the oral microbiome.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2013-01-01
description Oral infections have a strong ethnic predilection; suggesting that ethnicity is a critical determinant of oral microbial colonization. Dental plaque and saliva samples from 192 subjects belonging to four major ethnicities in the United States were analyzed using terminal restriction fragment length polymorphism (t-RFLP) and 16S pyrosequencing. Ethnicity-specific clustering of microbial communities was apparent in saliva and subgingival biofilms, and a machine-learning classifier was capable of identifying an individual's ethnicity from subgingival microbial signatures. The classifier identified African Americans with a 100% sensitivity and 74% specificity and Caucasians with a 50% sensitivity and 91% specificity. The data demonstrates a significant association between ethnic affiliation and the composition of the oral microbiome; to the extent that these microbial signatures appear to be capable of discriminating between ethnicities.
url http://europepmc.org/articles/PMC3806732?pdf=render
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