Image-based quantification of Candida albicans filamentation and hyphal length using the open-source visual programming language JIPipe.

The formation of hyphae is one of the most crucial virulence traits the human pathogenic fungus Candida albicans possesses. The assessment of hyphal length in response to various stimuli, such as exposure to human serum, provides valuable insights into the adaptation strategies of C. albicans to the host environment. Despite the increasing high-throughput capacity live-cell imaging and data generation, the accurate analysis of hyphal growth has remained a laborious, error-prone, and subjective manual process. We developed an analysis pipeline utilizing the open-source visual programming language Java Image Processing Pipeline (JIPipe) to overcome the limitations associated with manual analysis of hyphal growth. By comparing our automated approach with manual analysis, we refined the strategies to achieve accurate differentiation between yeast cells and hyphae. The automated method enables length measurements of individual hyphae, facilitating a time-efficient, high-throughput, and user-friendly analysis. By utilizing this JIPipe analysis approach, we obtained insights into the filamentation behavior of two C. albicans strains when exposed to human serum albumin (HSA), the most abundant protein in human serum. Our findings indicate that despite the known role of HSA in stimulating fungal growth, it reduces filamentous growth. The implementation of our automated JIPipe analysis approach for hyphal growth represents a long-awaited and time-efficient solution to meet the demand of high-throughput data generation. This tool can benefit different research areas investigating the virulence aspects of C. albicans.