bioRxivEvolutionary BiologyPreprint
Cross-Kingdom Control: Yeast Prion Protein Modulates Host Physiology in Drosophila
Chih-Chun LiniD, Jessica Y Jiang, Maushmi D Chitale, Elissa J. CosgroveiD, Alexandria Van ElgortiD, Asha M. JainiD, Julia C Kelso, Xinyue CuiiD, Nilay YapiciiD, Andrew G. ClarkiD
Abstract
Prions, once mainly studied for their pathogenic roles, are now gaining recognition as adaptive elements in microbial physiology. Over one-third of wild yeast isolates harbor prion proteins, yet their impact on host-microbe interactions remains poorly characterized. Given the ecological dominance of yeasts in the Drosophila mycobiome, we leveraged the Drosophila melanogaster-Saccharomyces cerevisiae system to investigate how the mycobiome-derived prion, [MRPL10+], modulates host physiology. We show that flies exposed to [MRPL10+] yeast exhibit significantly enhanced cold tolerance and increased locomotor activity. This effect persists with heat-killed yeast and diluted culture, suggesting a stable, potent bioactive factor. Using the genetically diverse Drosophila Global Diversity Lines (GDL), we identified natural variation in responsiveness to [MRPL10+] yeast. Genome-wide association and functional RNAi screening revealed a gut-brain signaling axis involving genes critical for digestion, intercellular communication, transcription regulation, and neural transmission. Notably, serotonin and octopamine pathways were essential for [MRPL10+]-induced changes in cold tolerance and locomotion, implicating neuromodulatory circuits in prion-mediated microbial signaling. Our findings establish a mechanistic link between a fungal prion and host metabolic and neural adaptation. This work provides the first genetic dissection of a prion-mediated host-microbe interaction, laying the groundwork for investigating beneficial prions in complex microbial communities and highlighting a new dimension of the mycobiomes influence on animal physiology.
- organism: Drosophila
- assay: proteomics
- research focus: cell type annotation
- approach: statistical model
- Citations
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