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

Scientific Reports
Ting L LuoAlexander H Rickard

Abstract

Biofilms are surface-attached microbial communities whose architecture can be captured with confocal microscopy. Manual or automatic thresholding of acquired images is often needed to help distinguish biofilm biomass from background noise. However, manual thresholding is subjective and current automatic thresholding methods can lead to loss of meaningful data. Here, we describe an automatic thresholding method designed for confocal fluorescent signal, termed the biovolume elasticity method (BEM). We evaluated BEM using confocal image stacks of oral biofilms grown in pooled human saliva. Image stacks were thresholded manually and automatically with three different methods; Otsu, iterative selection (IS), and BEM. Effects on biovolume, surface area, and number of objects detected indicated that the BEM was the least aggressive at removing signal, and provided the greatest visual and quantitative acuity of single cells. Thus, thresholding with BEM offers a sensitive, automatic, and tunable method to maintain biofilm architectural properties for subsequent analysis.

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Citations

Aug 7, 2019·International Journal of Molecular Sciences·Cristina Cattò, Francesca Cappitelli
Jan 6, 2021·Nature Microbiology·Raimo HartmannKnut Drescher

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Methods Mentioned

BETA
light microscopy

Software Mentioned

BEM
Bioflux TM
MatLab script
Otsu
COMSTAT
Matlab
IS
MatLab Exporter
Imaris
Microsphere

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