Quantifying the branching frequency of virtual filamentous microbes using fractal analysis

The productivity of an industrial fermentation process involving a filamentous microbe is heavily dependent on the morphological form adopted by the organism. The development of systems capable of rapidly and accurately characterizing morphology within a given process represents a significant challenge, as the complex phenotypes that are manifested are not easily quantified. Conventional parameters employed in these analyses are often of limited value, as they reveal little about the branching behavior of the organism; an important consideration given the demonstrated link between branching frequency and metabolite production. In this study, the influence of branching behavior on the spatial distribution of mycelia grown in silico is examined through fractal analysis. It is demonstrated that fractal dimension, quantified based on the frequency distribution of parameterized boundary curves, and lacunarity act as robust estimators of branching behavior. The analysis can, in theory, be applied to any morphological form, providing universally applicable process parameters for more complete data acquisition.