CRISPR-BASED MOLECULAR DETECTION OF FUNGAL PATHOGENS AFFECTING COMMERCIAL MUSHROOM CULTIVATION

Abstract

Commercial mushroom cultivation faces persistent threats from fungal pathogens including Trichoderma species (green mold), Lecanicillium fungicola (dry bubble), Mycogone perniciosa (wet bubble), and Cladobotryum species (cobweb disease), causing yield losses ranging from 20% to complete crop destruction. Current disease management strategies rely heavily on chemical fungicides and visual symptom recognition, yet both approaches are increasingly inadequate due to fungicide resistance development, regulatory restrictions, and the delayed manifestation of disease symptoms that appear only after irreversible yield loss and pathogen dissemination have occurred. This review critically examines the emerging application of CRISPR-Cas-based molecular diagnostics for rapid, on-site detection of fungal pathogens in commercial mushroom cultivation systems. The fundamental mechanisms of CRISPR-Cas diagnostic platforms, particularly Cas12a and Cas13a effectors that exhibit target-activated collateral cleavage activity, are explored alongside their integration with isothermal amplification technologies including Recombinase Polymerase Amplification (RPA) and Loop-Mediated Isothermal Amplification (LAMP). Key considerations for diagnostic assay development are addressed, including target genomic locus selection (ITS, TEF1-α, RPB2, β-tubulin), crRNA engineering parameters, off-target mitigation strategies, and the challenges posed by substrate-derived inhibitors such as humic acids and polysaccharides present in mushroom compost and casing materials. Comparative analysis reveals that CRISPR-Cas coupled isothermal biosensors achieve superior analytical specificity through dual-recognition architecture (isothermal primers plus crRNA verification), ultra-high sensitivity (1 fg/μL to 100 aM), and rapid turnaround times (25–50 minutes) while demonstrating tolerance to crude sample lysates and field-deployable point-of-care compatibility. This integrated molecular detection approach offers a transformative solution for early pathogen surveillance, facilitating timely biosecurity interventions and reducing economic losses in global mushroom production systems.