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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.
Original language | English |
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Article number | 44 |
Number of pages | 12 |
Journal | npj Biofilms and Microbiomes |
Volume | 7 |
Issue number | 1 |
DOIs | |
Publication status | Published - 14 May 2021 |
Bibliographical 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® (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).
Fingerprint
Dive into the research topics of 'Biofilm viability checker: an open-source tool for automated biofilm viability analysis from confocal microscopy images'. Together they form a unique fingerprint.Projects
- 2 Finished
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Process Design to Prevent Prosthetic Infections
Grover, L. (Principal Investigator), Attallah, M. (Co-Investigator), Webber, M. (Co-Investigator), Shepherd, D. (Co-Investigator), Cox, S. (Co-Investigator) & Gough, R. (Co-Investigator)
Engineering & Physical Science Research Council
1/09/17 → 28/02/21
Project: Research Councils
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Maximising cavitation to clean dental implants
Walmsley, D. (Principal Investigator) & Wang, Q. (Co-Investigator)
Engineering & Physical Science Research Council
1/07/17 → 31/05/21
Project: Research