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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Sustainable Perennial Crops Laboratory » Research » Publications at this Location » Publication #430350
Research Project: Development of Pathogen- and Plant-Based Genetic Tools and Disease Mitigation Methods for Tropical Perennial Crops

Location: Sustainable Perennial Crops Laboratory

Title: A geometric and probabilistic framework for mechanistic antifungal screening from colony morphology

Author
item Ahn, Ezekiel
item Baek, Insuck
item LIM, SEUNGHYUN - Orise Fellow
item Lovelace, Amelia
item Kazem Rostami, Masoud
item Lew, Helen
item Ashby, Richard
item CHA, MINHYEOK - Orise Fellow
item Kim, Moon
item Park, Sunchung
item Meinhardt, Lyndel

Submitted to: Pest Management Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 4/10/2026
Publication Date: 4/27/2026
Citation: Ahn, E.J., Baek, I., Lim, S., Lovelace, A.H., Kazem Rostami, M., Lew, H.N., Ashby, R.D., Cha, M., Kim, M.S., Park, S., Meinhardt, L.W. 2026. A geometric and probabilistic framework for mechanistic antifungal screening from colony morphology. Pest Management Science. https://doi.org/10.1002/ps.70860.
DOI: https://doi.org/10.1002/ps.70860

Interpretive Summary: When scientists develop new eco-friendly fungicides to protect crops like coffee and cacao, they typically rely on a single number (like "EC50") to measure "how much" the chemical stops fungal growth. However, this traditional method is blind to "how" the fungus actually dies—whether it simply stops growing or if its cell structure is physically destroyed. To solve this, we created a new "mechanistic map" that measures two things at once: the "Potency" (growth suppression) and the "Polarity" (shape distortion) of the fungus. We applied this new method to data from fungi treated with "amide" compounds derived from renewable sources like soybean oil. Our analysis revealed that these compounds do more than just stop growth; they actively "stretch" and "pinch" the fungal cells, a unique attack mode we identified as "polarity disruption." We also proved that this new map works for physical treatments like UV light, making it a universal translator for fungal stress. This research provides a powerful visual tool for chemists and plant pathologists to design smarter, more targeted green fungicides that are effective against resistant pathogens, ultimately supporting sustainable agriculture.

Technical Abstract: Antifungal screening typically relies on scalar metrics like EC50, which compress efficacy into a single value while discarding critical mechanistic information about colony morphology. We present a multi-dimensional framework that converts morphological data into a “grammar” of antifungal action: dose-free potency ('), polarity disruption or shape anisotropy (I), and event-level probability (p). By applying this framework to a dataset of diverse isolates treated with novel phenolic-branched amides and acids, we found that amide chemistries consistently occupy a distinct mechanistic quadrant characterized by high potency and significant polarity disruption (positive I). This “shape signal” was physically linked to a bidirectional contraction of the colony axes, identifying a specific geometric failure mode. We further validated this framework using an external UV-C dataset, demonstrating that the '–I–p grammar successfully captures dose-dependent stress responses across both chemical and physical modalities. This work replaces one-dimensional scalars with a device-agnostic, probabilistic map that enables the mechanistic classification of antifungal agents and the rigorous quantification of phenotypic responses.