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Plos One : Exploring the Dynamic Core Microbiome of Plaque Microbiota During Head-and-neck Radiotherapy Using Pyrosequencing, Volume 7

By Aziz, Ramy, K.

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Book Id: WPLBN0003937439
Format Type: PDF eBook :
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Reproduction Date: 2015

Title: Plos One : Exploring the Dynamic Core Microbiome of Plaque Microbiota During Head-and-neck Radiotherapy Using Pyrosequencing, Volume 7  
Author: Aziz, Ramy, K.
Volume: Volume 7
Language: English
Subject: Journals, Science, Medical Science
Collections: Periodicals: Journal and Magazine Collection (Contemporary)
Historic
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Publisher: Plos

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Aziz, R. K. (n.d.). Plos One : Exploring the Dynamic Core Microbiome of Plaque Microbiota During Head-and-neck Radiotherapy Using Pyrosequencing, Volume 7. Retrieved from http://netlibrary.net/


Description
Description : Radiotherapy is the primary treatment modality used for patients with head-and-neck cancers, but inevitably causes microorganism-related oral complications. This study aims to explore the dynamic core microbiome of oral microbiota in supragingival plaque during the course of head-and-neck radiotherapy. Eight subjects aged 26 to 70 were recruited. Dental plaque samples were collected (over seven sampling time points for each patient) before and during radiotherapy. The V1– V3 hypervariable regions of bacterial 16S rRNA genes were amplified, and the high-throughput pyrosequencing was performed. A total of 140 genera belonging to 13 phyla were found. Four phyla (Actinobacteria, Bacteroidetes, Firmicutes, and Proteobacteria) and 11 genera (Streptococcus, Actinomyces, Veillonella, Capnocytophaga, Derxia, Neisseria, Rothia, Prevotella, Granulicatella, Luteococcus, and Gemella) were found in all subjects, supporting the concept of a core microbiome. Temporal variation of these major cores in relative abundance were observed, as well as a negative correlation between the number of OTUs and radiation dose. Moreover, an optimized conceptual framework was proposed for defining a dynamic core microbiome in extreme conditions such as radiotherapy. This study presents a theoretical foundation for exploring a core microbiome of communities from time series data, and may help predict community responses to perturbation as caused by exposure to ionizing radiation.

 

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