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Biofilm viability checker: An open-source tool for automated biofilm viability analysis from confocal microscopy images

Quantifying biofilm formation on surfaces is challenging because traditional microbiological methods, such as total colony-forming units (CFUs), often rely on manual counting. These are laborious, resource intensive techniques, more susceptible to human error. Confocal laser scanning microscopy (CLS...

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Autores principales: Mountcastle, Sophie E., Vyas, Nina, Villapun, Victor M., Cox, Sophie C., Jabbari, Sara, Sammons, Rachel L., Shelton, Richard M., Walmsley, A. Damien, Kuehne, Sarah A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8121819/
https://www.ncbi.nlm.nih.gov/pubmed/33990612
http://dx.doi.org/10.1038/s41522-021-00214-7
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author Mountcastle, Sophie E.
Vyas, Nina
Villapun, Victor M.
Cox, Sophie C.
Jabbari, Sara
Sammons, Rachel L.
Shelton, Richard M.
Walmsley, A. Damien
Kuehne, Sarah A.
author_facet Mountcastle, Sophie E.
Vyas, Nina
Villapun, Victor M.
Cox, Sophie C.
Jabbari, Sara
Sammons, Rachel L.
Shelton, Richard M.
Walmsley, A. Damien
Kuehne, Sarah A.
author_sort Mountcastle, Sophie E.
collection PubMed
description Quantifying biofilm formation on surfaces is challenging because traditional microbiological methods, such as total colony-forming units (CFUs), often rely on manual counting. These are laborious, resource intensive techniques, more susceptible to human error. Confocal laser scanning microscopy (CLSM) is a high-resolution technique that allows 3D visualisation of biofilm architecture. In combination with a live/dead stain, it can be used to quantify biofilm viability on both transparent and opaque surfaces. However, there is little consensus on the appropriate methodology to apply in confocal micrograph processing. In this study, we report the development of an image analysis approach to repeatably quantify biofilm viability and surface coverage. We also demonstrate its use for a range of bacterial species and translational applications. This protocol has been created with ease of use and accessibility in mind, to enable researchers who do not specialise in computational techniques to be confident in applying these methods to analyse biofilm micrographs. Furthermore, the simplicity of the method enables the user to adapt it for their bespoke needs. Validation experiments demonstrate the automated analysis is robust and accurate across a range of bacterial species and an improvement on traditional microbiological analysis. Furthermore, application to translational case studies show the automated method is a reliable measurement of biomass and cell viability. This approach will ensure image analysis is an accessible option for those in the microbiology and biomaterials field, improve current detection approaches and ultimately support the development of novel strategies for preventing biofilm formation by ensuring comparability across studies.
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spelling pubmed-81218192021-05-17 Biofilm viability checker: An open-source tool for automated biofilm viability analysis from confocal microscopy images Mountcastle, Sophie E. Vyas, Nina Villapun, Victor M. Cox, Sophie C. Jabbari, Sara Sammons, Rachel L. Shelton, Richard M. Walmsley, A. Damien Kuehne, Sarah A. NPJ Biofilms Microbiomes Article Quantifying biofilm formation on surfaces is challenging because traditional microbiological methods, such as total colony-forming units (CFUs), often rely on manual counting. These are laborious, resource intensive techniques, more susceptible to human error. Confocal laser scanning microscopy (CLSM) is a high-resolution technique that allows 3D visualisation of biofilm architecture. In combination with a live/dead stain, it can be used to quantify biofilm viability on both transparent and opaque surfaces. However, there is little consensus on the appropriate methodology to apply in confocal micrograph processing. In this study, we report the development of an image analysis approach to repeatably quantify biofilm viability and surface coverage. We also demonstrate its use for a range of bacterial species and translational applications. This protocol has been created with ease of use and accessibility in mind, to enable researchers who do not specialise in computational techniques to be confident in applying these methods to analyse biofilm micrographs. Furthermore, the simplicity of the method enables the user to adapt it for their bespoke needs. Validation experiments demonstrate the automated analysis is robust and accurate across a range of bacterial species and an improvement on traditional microbiological analysis. Furthermore, application to translational case studies show the automated method is a reliable measurement of biomass and cell viability. This approach will ensure image analysis is an accessible option for those in the microbiology and biomaterials field, improve current detection approaches and ultimately support the development of novel strategies for preventing biofilm formation by ensuring comparability across studies. Nature Publishing Group UK 2021-05-14 /pmc/articles/PMC8121819/ /pubmed/33990612 http://dx.doi.org/10.1038/s41522-021-00214-7 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/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/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Mountcastle, Sophie E.
Vyas, Nina
Villapun, Victor M.
Cox, Sophie C.
Jabbari, Sara
Sammons, Rachel L.
Shelton, Richard M.
Walmsley, A. Damien
Kuehne, Sarah A.
Biofilm viability checker: An open-source tool for automated biofilm viability analysis from confocal microscopy images
title Biofilm viability checker: An open-source tool for automated biofilm viability analysis from confocal microscopy images
title_full Biofilm viability checker: An open-source tool for automated biofilm viability analysis from confocal microscopy images
title_fullStr Biofilm viability checker: An open-source tool for automated biofilm viability analysis from confocal microscopy images
title_full_unstemmed Biofilm viability checker: An open-source tool for automated biofilm viability analysis from confocal microscopy images
title_short Biofilm viability checker: An open-source tool for automated biofilm viability analysis from confocal microscopy images
title_sort biofilm viability checker: an open-source tool for automated biofilm viability analysis from confocal microscopy images
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8121819/
https://www.ncbi.nlm.nih.gov/pubmed/33990612
http://dx.doi.org/10.1038/s41522-021-00214-7
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