Chapter title |
Characterization of Sinus Microbiota by 16S Sequencing from Swabs
|
---|---|
Chapter number | 2 |
Book title |
Diagnostic Bacteriology
|
Published in |
Methods in molecular biology, June 2017
|
DOI | 10.1007/978-1-4939-7037-7_2 |
Pubmed ID | |
Book ISBNs |
978-1-4939-7035-3, 978-1-4939-7037-7
|
Authors |
Thad W. Vickery B.A., Jennifer M. Kofonow M.S., Vijay R. Ramakrishnan M.D., Vickery, Thad W., Kofonow, Jennifer M., Ramakrishnan, Vijay R., Thad W. Vickery, Jennifer Kofonow, Vijay R. Ramakrishnan, Jennifer M. Kofonow |
Editors |
Kimberly A. Bishop-Lilly |
Abstract |
New culture-independent microbiology methods are leading to a paradigm shift in our understanding of how the microbial community at the mucosal surface impacts sinonasal health and disease. Whereas traditional culture-based protocols were designed to identify specific pathogens in order to direct antibiotic therapies and eradicate bacteria, newer molecular techniques allow for the identification of both culturable and nonculturable bacteria in diverse communities. As a result of the recent explosion in the use of molecular techniques, we are gaining an understanding of how commensal bacteria may help modulate the host immune response and promote homeostasis. Here, we describe the general workflow of microbiome sequencing including the detailed methods for extracting mixed-community genomic DNA from sinonasal swabs, amplifying bacterial 16S rRNA genes using quantitative PCR, and preparing the samples for next-generation sequencing on the most commonly used sequencing platforms. |
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United States | 3 | 33% |
Ecuador | 1 | 11% |
Unknown | 5 | 56% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 9 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 27 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 5 | 19% |
Student > Bachelor | 4 | 15% |
Student > Ph. D. Student | 3 | 11% |
Student > Master | 3 | 11% |
Student > Doctoral Student | 2 | 7% |
Other | 5 | 19% |
Unknown | 5 | 19% |
Readers by discipline | Count | As % |
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Immunology and Microbiology | 6 | 22% |
Agricultural and Biological Sciences | 4 | 15% |
Biochemistry, Genetics and Molecular Biology | 3 | 11% |
Medicine and Dentistry | 3 | 11% |
Engineering | 2 | 7% |
Other | 2 | 7% |
Unknown | 7 | 26% |