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Van Elgort, A.

Publications and source records attributed to Van Elgort, A..

2 recordsLinked to original sources

Cross-Kingdom Control: Yeast Prion Protein Modulates Host Physiology in Drosophila

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.

evolutionary biology↗

Protein structure shapes natural genetic variation and de novo adaptation

Protein structural context strongly influences the functional outcomes of mutations, but exploiting this intuition to interpret the consequences of natural variants has been limited by the paucity of structural information. Here, we show that simple molecular heuristics based on predicted protein structures-solvent accessibility and the local complexity of the protein fold-are strong predictors of protein-coding variation in genomes from yeast to plants to humans. Polymorphisms in structured and unstructured regions alike were subject to these constraints, revealing fine-grained selection across amino acid residues and secondary structures. The same analyses distinguished deleterious variants in datasets from existing deep mutational scans. Extending the metrics to de novo adaptation, we developed a massively parallel directed evolution platform that isolated hundreds of independent adapted lineages within days. Optimized experimental conditions revealed dozens of rapamycin-resistant alleles of the FPR1/FKBP gene in a single experiment-resistance mutations that matched predictions from our structural heuristics. Together, these data demonstrate the power of a biochemical perspective to contextualize the functional landscape of both existing and newly arising genetic variation.

evolutionary biology↗