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Bang, J. K.

Publications and source records attributed to Bang, J. K..

2 recordsLinked to original sources

Membrane Tethering of Honeybee Antimicrobial Peptides in Drosophila Enhances Pathogen Defense at the Cost of Stress-Induced Host Vulnerability

Antimicrobial peptides (AMPs) represent a promising alternative to conventional antibiotics in combating multidrug-resistant pathogens, yet their clinical translation is hindered by proteolytic instability, cytotoxicity, and poor bioavailability. Here, we demonstrate that glycosylphosphatidylinositol (GPI)-mediated membrane tethering of honeybee defensin1 (Def1) in Drosophila melanogaster enhances its antimicrobial efficacy by [~]100-fold compared to secreted or untethered forms, while preserving physiological and behavioral integrity under baseline conditions. Using a genetically engineered Drosophila model, we expressed three Def1 variants: native (Def1), secreted (s-Def1), and membrane-tethered (t-Def1). Flies expressing t-Def1 exhibited superior bacterial clearance of Pseudomonas aeruginosa and improved survival post-infection, with no adverse effects on locomotion, courtship, or sleep architecture. However, under stress paradigms--including sleep deprivation and dextran sulfate sodium (DSS)-induced gut injury--t-Def1 exacerbated intestinal barrier dysfunction, as evidenced by elevated Smurf phenotype incidence, highlighting a trade-off between antimicrobial potency and epithelial vulnerability. Our work establishes Drosophila as a powerful platform for dissecting AMP mechanisms and engineering spatially targeted therapies, offering translational insights for pollinator health and human infectious disease management. These results advocate for iterative refinement of membrane-anchoring strategies to balance therapeutic efficacy with host safety, advancing the development of next-generation AMPs with minimized off-target effects.

biochemistry↗

Leveraging Drosophila Models to Explore AI-generated Synthetic Peptide's Potential in Boosting Honeybee Health and Resilience

The integration of artificial intelligence (AI) and machine learning (ML) in peptide design has revolutionized the development of antimicrobial peptides (AMPs), which are essential components of innate immunity. In this study, we identified a novel synthetic peptide, PAN4 (GAYTFKIRRK), through genetic screening of AI-generated candidates in Drosophila melanogaster. PAN4 demonstrated robust antimicrobial activity, stress tolerance, and antitumor effects, significantly enhancing survival rates following bacterial infections and improving locomotor behaviors without adversely affecting lifespan. Furthermore, PAN4 expression in intestinal stem cells completely suppressed RasV12-induced tumor progression, indicating its potential role in cancer prevention. The peptide also mitigated gut barrier dysfunction associated with sleep deprivation and reduced inflammation in a dextran sulfate sodium (DSS)-induced colitis model. Mechanistically, PAN4s antimicrobial activity was linked to its interaction with specific peptidoglycan recognition proteins (PGRPs), particularly PGRP-SC1a, while the Tak1-mediated immune signaling pathway was found to be non-essential for its efficacy. PAN4 showed promising effects on honeybee health, enhancing survival rates under bacterial stress. Furthermore, PAN4 expression demonstrated significant anti-tumor activity in the Drosophila gut tumor model. Our findings suggest that PAN4 serves as a versatile agent with significant implications for enhancing immune responses and combating diseases in honeybee populations, paving the way for future applications in agriculture and medicine.

genetics↗