Back

Mutations in antimicrobial peptides differently affect sleep and plasticity

Kumar, R.; Madhav, G.; Balasubramanian, P.; Lakhiani, R.; Joshi, M.; Jaggi, V.; Pal, A.; Khan, I.; Melnattur, K.

2025-09-30 neuroscience
10.1101/2025.09.28.679065 bioRxiv
Show abstract

Molecules implicated in host defense can, independent of their roles as immune mediators, regulate sleep. In mammals, cytokines such as Tumor Necrosis Factor (TNF ) and Interleukin 1{beta} (IL1{beta}) promote sleep. In Drosophila, infection stimulates the systemic release of a battery of anti-microbial peptides (AMPs). These fly immune effectors have been understudied as sleep modulators. We obtained mutants in different AMPs and characterized their functions in sleep and sleep dependent outputs. AMP mutants sleep less with a longer sleep latency, and lowered arousal thresholds. Group C mutant flies, doubly mutant for the anti-fungal peptides Metchinikowin (Mtk) and Drosomycin (Drs), showed the greatest impairments. These Group C mutants also showed an exaggerated sleep rebound. Sleep rebound was unaltered in other mutants. Different sets of AMP mutants exhibited specific disruptions in socialization and rocking induced sleep. These data are a detailed characterization of sleep regulation in AMP mutants. We also evaluated sleep functions. Group C mutants uniquely exhibited normal learning and memory, and lower synapse abundance, despite sleeping the least. Group C mutants are thus able to carry out some sleep functions without sleeping very much. Glial knockdown of Metchnikowin and Drosomycin mimicked the sleep phenotypes of the null mutants, these genes thus act from glia. Sleep and memory defects in AMP mutants was reversible - enhancing sleep of Bomanin mutants pharmacologically or behaviorally improved learning and memory. Together, these data suggest that AMPs are potent sleep modulators and that different classes of AMPs differently affect sleep and sleep dependent outcomes.

Matching journals

The top 4 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.