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

Abstract

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.