EPSRC Centre for Doctoral Training in Physical Sciences for Health, University of Birmingham, Edgbaston, Birmingham, UK.
School of Dentistry, University of Birmingham, 5 Mill Pool Way, Birmingham, UK.
NPJ Biofilms Microbiomes. 2021 May 14;7(1):44. doi: 10.1038/s41522-021-00214-7.
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.
量化表面生物膜的形成具有挑战性,因为传统的微生物学方法(如总菌落形成单位(CFU))通常依赖于手动计数。这些方法既费力又耗费资源,更容易出现人为错误。共焦激光扫描显微镜(CLSM)是一种高分辨率技术,可用于 3D 可视化生物膜结构。结合活/死染色,可以用于量化透明和不透明表面上生物膜的活力。然而,在共焦显微镜处理方面,对于适当的方法学几乎没有共识。在本研究中,我们报告了一种图像分析方法的开发,该方法可重复定量生物膜的活力和表面覆盖率。我们还展示了它在一系列细菌物种和转化应用中的用途。该方案旨在易于使用和易于访问,以使不专门从事计算技术的研究人员有信心将这些方法应用于分析生物膜显微镜图像。此外,该方法的简单性使用户能够根据自己的需求进行调整。验证实验表明,自动化分析在一系列细菌物种中具有稳健性和准确性,优于传统的微生物学分析。此外,在转化案例研究中的应用表明,自动化方法是生物量和细胞活力的可靠测量方法。这种方法将确保图像分析成为微生物学和生物材料领域的一种可访问的选择,改进当前的检测方法,并最终通过确保研究之间的可比性来支持预防生物膜形成的新策略的开发。