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Modeling Oral Multispecies Biofilm Recovery After Antibacterial Treatment

Recovery of multispecies oral biofilms is investigated following treatment by chlorhexidine gluconate (CHX), iodine-potassium iodide (IPI) and Sodium hypochlorite (NaOCl) both experimentally and theoretically. Experimentally, biofilms taken from two donors were exposed to the three antibacterial sol...

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Autores principales: Jing, Xiaobo, Huang, Xiangya, Haapasalo, Markus, Shen, Ya, Wang, Qi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6349915/
https://www.ncbi.nlm.nih.gov/pubmed/30692576
http://dx.doi.org/10.1038/s41598-018-37170-w
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author Jing, Xiaobo
Huang, Xiangya
Haapasalo, Markus
Shen, Ya
Wang, Qi
author_facet Jing, Xiaobo
Huang, Xiangya
Haapasalo, Markus
Shen, Ya
Wang, Qi
author_sort Jing, Xiaobo
collection PubMed
description Recovery of multispecies oral biofilms is investigated following treatment by chlorhexidine gluconate (CHX), iodine-potassium iodide (IPI) and Sodium hypochlorite (NaOCl) both experimentally and theoretically. Experimentally, biofilms taken from two donors were exposed to the three antibacterial solutions (irrigants), respectively, for 10 minutes. We observe that (a) live bacterial cell ratios decline for a week after the exposure and the trend then reverses beyond the week; after fifteen weeks, live bacterial cell ratios in biofilms fully return to their pretreatment levels; (b) NaOCl is shown as the strongest antibacterial agent for the oral biofilms; (c) multispecies oral biofilms from different donors showed no difference in their susceptibility to all the bacterial solutions. Guided by the experiment, a mathematical model for biofilm dynamics is developed, accounting for multiple bacterial phenotypes, quorum sensing, and growth factor proteins, to describe the nonlinear time evolutionary behavior of the biofilms. The model captures time evolutionary dynamics of biofilms before and after antibacterial treatment very well. It reveals the important role played by quorum sensing molecules and growth factors in biofilm recovery and verifies that the source of biofilms has a minimal effect to their recovery. The model is also applied to describe the state of biofilms of various ages treated respectively by CHX, IPI and NaOCl, taken from different donors. Good agreement with experimental data predicted by the model is obtained as well, confirming its applicability to modeling biofilm dynamics in general.
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spelling pubmed-63499152019-01-30 Modeling Oral Multispecies Biofilm Recovery After Antibacterial Treatment Jing, Xiaobo Huang, Xiangya Haapasalo, Markus Shen, Ya Wang, Qi Sci Rep Article Recovery of multispecies oral biofilms is investigated following treatment by chlorhexidine gluconate (CHX), iodine-potassium iodide (IPI) and Sodium hypochlorite (NaOCl) both experimentally and theoretically. Experimentally, biofilms taken from two donors were exposed to the three antibacterial solutions (irrigants), respectively, for 10 minutes. We observe that (a) live bacterial cell ratios decline for a week after the exposure and the trend then reverses beyond the week; after fifteen weeks, live bacterial cell ratios in biofilms fully return to their pretreatment levels; (b) NaOCl is shown as the strongest antibacterial agent for the oral biofilms; (c) multispecies oral biofilms from different donors showed no difference in their susceptibility to all the bacterial solutions. Guided by the experiment, a mathematical model for biofilm dynamics is developed, accounting for multiple bacterial phenotypes, quorum sensing, and growth factor proteins, to describe the nonlinear time evolutionary behavior of the biofilms. The model captures time evolutionary dynamics of biofilms before and after antibacterial treatment very well. It reveals the important role played by quorum sensing molecules and growth factors in biofilm recovery and verifies that the source of biofilms has a minimal effect to their recovery. The model is also applied to describe the state of biofilms of various ages treated respectively by CHX, IPI and NaOCl, taken from different donors. Good agreement with experimental data predicted by the model is obtained as well, confirming its applicability to modeling biofilm dynamics in general. Nature Publishing Group UK 2019-01-28 /pmc/articles/PMC6349915/ /pubmed/30692576 http://dx.doi.org/10.1038/s41598-018-37170-w Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Jing, Xiaobo
Huang, Xiangya
Haapasalo, Markus
Shen, Ya
Wang, Qi
Modeling Oral Multispecies Biofilm Recovery After Antibacterial Treatment
title Modeling Oral Multispecies Biofilm Recovery After Antibacterial Treatment
title_full Modeling Oral Multispecies Biofilm Recovery After Antibacterial Treatment
title_fullStr Modeling Oral Multispecies Biofilm Recovery After Antibacterial Treatment
title_full_unstemmed Modeling Oral Multispecies Biofilm Recovery After Antibacterial Treatment
title_short Modeling Oral Multispecies Biofilm Recovery After Antibacterial Treatment
title_sort modeling oral multispecies biofilm recovery after antibacterial treatment
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6349915/
https://www.ncbi.nlm.nih.gov/pubmed/30692576
http://dx.doi.org/10.1038/s41598-018-37170-w
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