Ecophysiology of Fusarium species under environmental constraints

Garcia M, Mahmoud R, Bancal M, Bancal P, Bernillon S, Pinson-Gadais L, Richard-Forget F, Foulongne-Oriol M. (2025). Ecophysiological behavior of major Fusarium species in response to combinations of temperature and water activity constraints. Appl Environ Microbiol 0:e01832-24. https://doi.org/10.1128/aem.01832-24

ABSTRACT Fusarium head blight (FHB) is a devastating fungal disease affectingcereals, caused by Fusarium species that can produce harmful mycotoxins. Fusarium species coexist within the same ecological niche during infection, with their population dynamics and associated mycotoxin patterns strongly influencedby the environment. This study provides a comprehensive investigation of the ecophysiological responses of the major Fusarium species causing FHB under varying abiotic factors. We assessed growth and mycotoxin production of differentisolates of Fusarium avenaceum, Fusarium graminearum, Fusarium langsethiae, Fusarium poae, and Fusarium tricinctum under 24 combinations of temperature (θ = 15, 20, 25, 30°C) and water activity levels (aw = 0.99, 0.98, 0.97, 0.96, 0.95, 0.94). Our findingsindicated that θ, aw, and their interaction have a main significantimpact on species behavior. Thanks to innovative statistical approaches using fungal growth data from optical density measurements and mycotoxin quantification,we demonstrated significantinter- and intra-specificdifferencesin environmental responses. Growth and mycotoxin production of F. graminearum and F. avenaceum appeared favored under high temperature (≥25°C) and high water activity (≥0.97), whereas lower aw levels (≥0.95) were also conducive for F. poae and F. tricinctum. A specificand unique behavior of F. langsethiae to lowest temperatures (≤20°C) was highlighted. Understanding the ecophysiological requirements of Fusarium species is crucial in the context of climate change, which is expected to worsen disease outbreaks. This study provides valuable knowledge for improving the reliability and robustness of FHB prediction models and anticipating the associated mycotoxin risk.