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

Area of Science:

• Medical Mycology
• Computational Biology
• Biophysics

Background:

• Hyphal formation is a key virulence factor for the human pathogenic fungus Candida albicans.
• Analyzing hyphal growth is crucial for understanding C. albicans adaptation but is traditionally manual, laborious, and subjective.
• High-throughput live-cell imaging generates vast data, necessitating automated analysis methods.

Purpose of the Study:

• To develop and validate an automated image analysis pipeline for Candida albicans hyphal growth using JIPipe.
• To enable accurate, efficient, and high-throughput quantification of hyphal length and differentiation.
• To investigate the effect of human serum albumin (HSA) on C. albicans filamentation.

Main Methods:

• Development of an automated image analysis workflow in Java Image Processing Pipeline (JIPipe).
• Comparative analysis of the automated method against manual measurements for accuracy and reliability.
• Application of the JIPipe pipeline to assess hyphal growth of C. albicans strains exposed to human serum albumin (HSA).

Main Results:

• The JIPipe pipeline accurately differentiates between yeast and hyphal forms of C. albicans.
• Automated analysis provides efficient, high-throughput measurement of individual hyphal lengths.
• Exposure to HSA, despite stimulating fungal growth, significantly reduced filamentation in C. albicans.

Conclusions:

• The automated JIPipe pipeline offers a time-efficient and user-friendly solution for analyzing C. albicans hyphal growth.
• This tool addresses the need for high-throughput analysis in live-cell imaging studies of fungal virulence.
• Findings reveal a novel inhibitory effect of HSA on C. albicans filamentous growth, impacting virulence studies.