Analysis of Biofilm Complexity in 3D (ABC3D): An open-source framework for quantitative fractal, textural, and statistical analysis of colony biofilm morphology in three dimensions

Abstract

2.Quantitative image analysis is central to understanding microbial growth, morphology, and spatial organisation. However, conventional metrics such as mean intensity or object count often do not capture the complex structural heterogeneity and patterning characteristic of microbial colonies and biofilms. To address this limitation, Analysis of Biofilm Complexity in 3D (ABC3D), an open-source Python framework for automated extraction of fractal, textural, and statistical descriptors from volumetric microscopy images, is reported. ABC3D computes a set of parameters including fractal dimension, lacunarity, entropy, grey-level co-occurrence matrix features, and wavelet sub-band energies from three-dimensional (3D) image datasets. ABC3D is demonstrated in macrocolony biofilms formed by cell shape mutants of Escherichia coli, where it is shown that nutrient availability accounts for the majority of structural variance, while cell shape produces additional structural variation that differs between nutrient conditions. ABC3D provides researchers with an accessible, quantitative approach to assessing biofilm morphology in microscopy datasets. SummaryAn open-source, quantitative analysis pipeline is presented that integrates fractal, lacunarity, entropy, texture and wavelet descriptors to characterise colony biofilm architecture in three dimensions. Application to Escherichia coli cell shape mutants demonstrates that macrocolony biofilm architecture is best understood as a coordinated, multiscale phenotype rather than as an aggregate of independent structural metrics. 3. Impact statementBiofilm architecture is pivotal for microbial survival, antimicrobial tolerance, and ecological function but tools to quantify structural organisation in these cell communities remain limited. The commonest metrics describe bulk properties such as width, thickness, or cell number, but they do not capture multiscale spatial heterogeneity. Here, an open-source framework for Analysis of Biofilm Complexity in 3 Dimensions (ABC3D) is reported. This software integrates measurements of fractal geometry, lacunarity, entropy, texture statistics, and wavelet energy. ABC3D is demonstrated in Escherichia coli macrocolony biofilms, where it is shown that nutrient environment has a leading role in determining colony architecture in E. coli biofilms, while cell shape has a lesser but still significant influence on structural variation. The ABC3D pipeline can be applied to any microbial communities imaged by confocal microscopy and other volumetric imaging methods and has the potential to give a deeper understanding of how cells organise in biofilms. 4. Data summaryFull code for ABC3D and data analysis is available at https://github.com/gailmcconnell/ABC3D. Image data are available upon request. The author confirms all supporting data, code and protocols have been provided within the article or through supplementary data files.