Image Analysis Characterizes Phenotypic Variation in the Growth of Mushroom‐Forming Fungus Schizophyllum commune

Abstract

Schizophyllum commune, a common wood‐decay mushroom known for its extremely high genetic variation and as a rare cause of human respiratory diseases, could be a promising model fungus contributing to both biology and medicine. To better understand its phenotypic variation, we developed an image analysis system that quantifies morphological and physiological traits of mycelial colonies in Petri dishes. This study evaluated growth of six wild and one clinical isolates of Japanese S. commune, subjected to different temperatures and glucose concentrations, including a condition mimicking the human respiratory environment. Our analysis revealed that combinations of two growth indices, area and whiteness, and profiling by clustering algorithms highlighted strain‐specific responses. For example, the clinical isolate was the whitest under the respiratory‐like condition. We also found that the growth rate was strongly determined by glucose concentration, while the effects of temperature on growth varied among the strains, suggesting that while glucose preference is common in this species, responses to temperature differ between strains. This system showed sufficient sensitivity to detect variation in mycelial growth. Our study provides a key to unraveling morphological and physiological traits behind the high polymorphisms in S. commune, including the ability to colonize the human respiratory tract.