A variety of insect pests pose a serious threat to global cotton production. Among these, pink bollworm (PBW) and whiteflies are the most devastating, resulting in substantial yield losses and increased pesticide use. Conventional insect-resistance strategies, which primarily rely on single Bacillus thuringiensis (Bt) genes, often face limitations due to the development of resistance in target pests. To overcome these challenges, the fusion of multiple insecticidal proteins, including Bt toxins and plant-derived lectins, offers a synergistic approach to broaden the spectrum and durability of resistance. The modular insecticidal scaffold exhibited a distinct promoter-dependent expression pattern, highlighting its potential as a customisable platform for targeted cotton protection. Molecular docking revealed favorable interactions of Cry1Ac, Cry1Ab, Vip3A with the pink bollworm cadherin receptor, whereas ASAL showed favorable binding to mannose residues, representing its recognition of mannose-containing glycoconjugates on midgut cells, supporting the structural compatibility of the de novo assembled scaffold. The scaffold carrying these domains was synthesised and cloned into the pCAMBIA1302 vector under constitutive and fibre-specific promoters, and subsequently transformed into a local cotton variety. Transgenic lines harbouring the fibre-specific promoter (GhSCFP) displayed significantly elevated expression in bolls, reaching over a 100-fold increase compared with leaves, whereas the constitutive promoter (CaMV35S) drove higher expression in foliage, consistent with its broader activity profile. Promoter-guided expression patterns strongly influenced insecticidal outcomes: fibre-specific lines showed substantial mortality in PBW (up to 90–95%), whereas constitutive promoter-driven lines exhibited greater suppression of whiteflies (approximately 60–70%). The observed correlation between spatial expression and pest-specific lethality indicates that the scaffold functions as a cohesive insecticidal unit, effectively integrating multiple toxin domains while maintaining spatial regulation. This dual strategy of boll-targeted PBW protection and whole-plant whitefly resistance represents a significant advancement over single-gene Bt approaches, providing a more resilient and comprehensive resistance framework for cotton improvement. Our findings indicate that promoter selection is a crucial factor influencing tissue-specific expression and insecticidal efficacy. The synergistic combination of fibre-specific and constitutive promoters establishes a dual framework for targeted boll protection and broader pest management. This modular, promoter-driven approach holds considerable promise for the development of next-generation, sustainable pest-resistant cotton suitable for integrated pest management strategies.
Crystalline (Cry) δ-endotoxins from Bacillus thuringiensis (Bt) have supported microbial and transgenic insect control for decades, but field-evolved resistance and natural tolerance in important pests have increased interest in complementary insecticidal proteins. Vegetative insecticidal proteins (Vips), secreted duri...
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Insecticide bioassays conducted across major cotton-growing regions of India revealed a notable increase in LC50 values in field populations compared to the laboratory-susceptible strain, confirming reduced susceptibility and development of resistance.
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The pink bollworm (Pectinophora gossypiella) is one of the most destructive pests of cotton worldwide, causing substantial yield losses and economic damage. The deployment of Bt cotton expressing insecticidal proteins from Bacillus thuringiensis (Bt), including Cry1Ac in Bollgard I (BG-I) and Cry1Ac plus Cry2Ab in Boll...
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Gray mold caused by Botrytis cinerea poses severe threats to global horticultural production. Conventional chemical fungicides face mounting restrictions due to rising pathogen resistance and stringent food safety regulations, creating an urgent need for sustainable alternatives. RNA pesticides offer an eco-friendly...
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A new machine-learning framework aims to improve the success rate of computational protein design while moving away from results that reproduce sequences found in nature.