A Systematic Method for Analysing Germination of Aspergillus Conidia Using Real-Time Imaging

Live cell imaging is a useful tool for studying community interactions, morphological development, and population variance in microbial research. Here, we aim to develop a new approach to monitor the time until germination and the hyphal development rate of filamentous fungi at an individual level. Conidia of 19 Aspergillus species, including some xerophilic, were suspended in liquid Sabouraud medium, and conidia were tracked for 96 h using real-time imaging. A sorting algorithm was developed to categorize conidia into germinated or non-germinated pools based on a decrease in circularity and an increase in area. The increase in area used in the sorting algorithm was species-specific and was derived using segmented linear regression to determine the inflection point of area increase, which served as a proxy for the transition from isotropic to polarized growth. Of the 19 species measured, 15 germinated within 96 h. In the germinated species, we measured the hyphal growth rate until the experiment termination or until conidia exited the imaging frame. Hyphal growth rates were calculated both on the individual conidium level and using growth models on data from the first 24 h post germination. This methodology enabled a high-throughput, species-specific, and individual approach when comparing germination metrics. The live-cell imaging approach for monitoring fungal germination and hyphal growth rate provides an important framework for studying fungal development and has the potential to offer in-depth insights into early fungal growth that may be overlooked by conventional endpoint assays.