A quantitative framework for multiscale analysis of Candida albicans biofilm development

Candida albicans is an opportunistic fungal pathogen of significant biomedical concern. Its ability to colonize abiotic surfaces of clinical devices — such as catheters and airway management systems — can result in life-threatening sepsis, especially in immunocompromised patients. A deeper understanding of C. albicans biofilm development under different environmental conditions is essential for improving antifungal treatments. In this study, we develop and validate a multiscale quantitative framework for analysing biofilm development. We examine C. albicans biofilm formation using live fluorescence microscopy across multiple scales and modalities, and introduce new quantification approaches. High-magnification tracking of hyphal tips reveals that hyphal elongation occurs intermittently rather than continuously. Using a new automated tracking approach, we show that hyphal emergence is initially rapid and slows down after approximately two hours. At lower magnifications, area coverage across large fields of view proves to be a robust and scalable metric. It is strongly influenced by seed density and extends analysis to later stages of growth. Elevated carbon dioxide levels significantly accelerate area coverage, promoting rapid biofilm expansion. Blue light illumination reduces C. albicans growth in a dose-dependent manner. Light-sheet imaging enables the long-term capture of vertical biofilm growth, complementing widefield-based approaches. We introduce logistic model parameters to effectively quantify the dynamics of surface area growth. The methodologies presented here are well-suited for high-content screening applications aimed at identifying compounds that inhibit or suppress fungal biofilm formation under clinically relevant conditions. • Multiscale image-based quantification of biofilm development. • New approaches for fluorescence microscopy of C. albicans growth. • Validated metrics for different developmental stages and conditions. • Methods are rapid, robust and suitable for screening applications.