A Sensitive Thresholding Method for Confocal Laser Scanning Microscope Image Stacks of Microbial Biofilms

Area of Science:

• Microbiology
• Microscopy
• Biofilm research

Background:

• Biofilms are microbial communities crucial in various environments.
• Confocal microscopy captures biofilm architecture, but image thresholding is challenging.
• Existing methods for image thresholding can be subjective or remove vital data.

Purpose of the Study:

• To introduce and evaluate the biovolume elasticity method (BEM) for automatic thresholding of confocal microscopy images of biofilms.
• To compare BEM with manual thresholding and other automatic methods (Otsu, iterative selection).
• To assess the impact of thresholding on biofilm biovolume, surface area, and object detection.

Main Methods:

• Developed the biovolume elasticity method (BEM) for automatic thresholding of confocal fluorescent signals.
• Applied BEM, Otsu, and iterative selection (IS) to confocal image stacks of oral biofilms.
• Compared quantitative metrics (biovolume, surface area, object count) and visual acuity across methods.

Main Results:

• BEM demonstrated the least aggressive signal removal compared to Otsu and IS.
• BEM provided superior visual and quantitative acuity of individual cells within the biofilm.
• The method preserved essential biofilm architectural properties for analysis.

Conclusions:

• The biovolume elasticity method (BEM) is a sensitive, automatic, and tunable approach for biofilm image analysis.
• BEM enhances the accurate quantification of biofilm structure and cellular components.
• This method improves the reliability of downstream analyses of microbial community architecture.