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Type: Journal article
Title: The microbial abundance dynamics of the paediatric oral cavity before and after sleep
Author: Carlson-Jones, J.A.P.
Kontos, A.
Kennedy, J.
Martin, A.
Lushington, K.
McKerral, J.
Paterson, J.S.
Smith, R.J.
Dann, L.M.
Speck, P.
Mitchell, J.G.
Citation: Journal of Oral Microbiology, 2020; 12(1):1741254-1-1741254-12
Publisher: Taylor & Francis
Issue Date: 2020
ISSN: 2000-2297
Statement of
Jessica A.P. Carlson-Jones, Anna Kontos, Declan Kennedy, James Martin, Kurt Lushington, Jody McKerral, James S. Paterson, Renee J. Smith, Lisa M. Dann, Peter Speck and James G. Mitchell
Abstract: Objective: Microhabitats in the oral cavity differ in microbial taxonomy. However, abundance variations of bacterial and viral communities within these microhabitats are not fully understood. Aims and Hypothesis: To assess the spatial distribution and dynamics of the microbial abundances within 6 microhabitats of the oral cavity before and after sleep. We hypothesise that the abundance distributions of these microbial communities will differ among oral sites. Methods: Using flow cytometry, bacterial and virus-like particle (VLP) abundances were enumerated for 6 oral microhabitats before and after sleep in 10 healthy paediatric sleepers. Results: Bacterial counts ranged from 7.2 ± 2.8 × 10⁵ at the palate before sleep to 1.3 ± 0.2 × 10⁸ at the back of the tongue after sleep, a difference of 187 times. VLPs ranged from 1.9 ± 1.0 × 10⁶ at the palate before sleep to 9.2 ± 5.0 × 10⁷ at the back of the tongue after sleep, a difference of 48 times. Conclusion: The oral cavity is a dynamic numerically heterogeneous environment where microbial communities can increase by a count of 100 million during sleep. Quantification of the paediatric oral microbiome complements taxonomic diversity information to show how biomass varies and shifts in space and time.
Keywords: Oral microbiome; sleep; flow cytometry; bacteria; viruses
Rights: © 2020 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
DOI: 10.1080/20002297.2020.1741254
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