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

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@article{4ca85e0c118e496883db6eaaff22c65e,
title = "Biofilm viability checker: an open-source tool for automated biofilm viability analysis from confocal microscopy images",
abstract = "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.",
author = "Sophie Mountcastle and Nina Vyas and Villapun, {Victor M.} and Sophie Cox and Sara Jabbari and Rachel Sammons and Richard Shelton and Damien Walmsley and Sarah Kuehne",
note = "Funding Information: The authors would like to thank Sandeep Shirgill and Imaan Griffiths for providing images of P. aeruginosa and multi-species F. nucleatum biofilms for testing the image analysis protocol, and Qianyin Mai for providing images of mouthwash treated biofilms. We acknowledge the use of BioRender{\textregistered} (BioRender.com) during image preparation of Supplementary Fig. 1. EPSRC provided funding through a studentship at the Centre for Doctoral Training in Physical Sciences for Health (EP/L016346/1) and through the grants EP/P015743/1 and EP/P02341X/1 (Process Design to Prevent Prosthetic Infections, PREVENT). The funding body were not involved in the writing of the manuscript and in the decision to submit the manuscript for publication. Publisher Copyright: {\textcopyright} 2021, The Author(s).",
year = "2021",
month = may,
day = "14",
doi = "10.1038/s41522-021-00214-7",
language = "English",
volume = "7",
journal = "npj Biofilms and Microbiomes",
issn = "2055-5008",
publisher = "Nature Publishing Group",
number = "1",

}

RIS

TY - JOUR

T1 - Biofilm viability checker

T2 - an open-source tool for automated biofilm viability analysis from confocal microscopy images

AU - Mountcastle, Sophie

AU - Vyas, Nina

AU - Villapun, Victor M.

AU - Cox, Sophie

AU - Jabbari, Sara

AU - Sammons, Rachel

AU - Shelton, Richard

AU - Walmsley, Damien

AU - Kuehne, Sarah

N1 - Funding Information: The authors would like to thank Sandeep Shirgill and Imaan Griffiths for providing images of P. aeruginosa and multi-species F. nucleatum biofilms for testing the image analysis protocol, and Qianyin Mai for providing images of mouthwash treated biofilms. We acknowledge the use of BioRender® (BioRender.com) during image preparation of Supplementary Fig. 1. EPSRC provided funding through a studentship at the Centre for Doctoral Training in Physical Sciences for Health (EP/L016346/1) and through the grants EP/P015743/1 and EP/P02341X/1 (Process Design to Prevent Prosthetic Infections, PREVENT). The funding body were not involved in the writing of the manuscript and in the decision to submit the manuscript for publication. Publisher Copyright: © 2021, The Author(s).

PY - 2021/5/14

Y1 - 2021/5/14

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=85105855062&partnerID=8YFLogxK

U2 - 10.1038/s41522-021-00214-7

DO - 10.1038/s41522-021-00214-7

M3 - Article

C2 - 33990612

VL - 7

JO - npj Biofilms and Microbiomes

JF - npj Biofilms and Microbiomes

SN - 2055-5008

IS - 1

M1 - 44

ER -