Image Analysis Characterizes Phenotypic Variation in the Growth of Mushroom‐Forming Fungus <i>Schizophyllum commune</i>

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.

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Publication Details

Journal
Genes to Cells
Published
2024-11-26
DOI
https://doi.org/10.1111/gtc.13181
Citations
1
Primary Topic
Fungal Biology and Applications
Type
article
Field-Weighted Citation Impact
0.45

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article

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

Hiromi Matsumae, Tadashi Imanishi, Megumi Sudo, Tsuyoshi Hosoya
1 citations
Genes to Cells
Fungal Biology and Applications
0.45
article

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

Hiromi Matsumae, Tadashi Imanishi, Megumi Sudo, Tsuyoshi Hosoya
article en
1 citations

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.

Genes to CellsVol. 30(1)
Tokai University (JP), National Museum of Nature and Science (JP)
Research Organization of Information and Systems, Japan Society for the Promotion of Science
Life in Land
Openalex Percentile: Top 30%
Fungal Biology and Applications
0.45
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Image Analysis Characterizes Phenotypic Variation in the Growth of Mushroom‐Forming Fungus <i>Schizophyllum commune</i> — Hiromi Matsumae, Tadashi Imanishi, et al. · Genes to Cells (2024) | TGRS Research Map | TGRS