title: Can yeast (S. cerevisiae) metabolic volatiles provide polymorphic signaling?
abstract: Chemical signaling between organisms is a ubiquitous and evolutionarily dynamic process that helps to ensure mate recognition, location of nutrients, avoidance of toxins, and social cooperation. Evolutionary changes in chemical communication systems progress through natural variation within the organism generating the signal as well as the responding individuals. A promising yet poorly understood system with which to probe the importance of this variation exists between D. melanogaster and S. cerevisiae. D. melanogaster relies on yeast for nutrients, while also serving as a vector for yeast cell dispersal. Both are outstanding genetic and genomic models, with Drosophila also serving as a preeminent model for sensory neurobiology. To help develop these two genetic models as an ecological model, we have tested if - and to what extent - S. cerevisiae is capable of producing polymorphic signaling through variation in metabolic volatiles. We have carried out a chemical phenotyping experiment for 14 diverse accessions within a common garden random block design. Leveraging genomic sequences for 11 of the accessions, we ensured a genetically broad sample and tested for phylogenetic signal arising from phenotypic dataset. Our results demonstrate that significant quantitative differences for volatile blends do exist among S. cerevisiae accessions. Of particular ecological relevance, the compounds driving the blend differences (acetoin, 2-phenyl ethanol and 3-methyl-1-butanol) are known ligands for D. melanogasters chemosensory receptors, and are related to sensory behaviors. Though unable to correlate the genetic and volatile measurements, our data point clear ways forward for behavioral assays aimed at understanding the implications of this variation.
authors.affiliation: Department of Molecular Biology and Genetics, Cornell University, Ithaca, New York, United States of America.
authors.forename: J Roman
authors.initials: JR
authors.lastname: Arguello
authors.forename: Carolina
authors.initials: C
authors.lastname: Sellanes
authors.forename: Yann Ru
authors.initials: YR
authors.lastname: Lou
authors.forename: Robert A
authors.initials: RA
authors.lastname: Raguso
mesh_terms: D000093:Acetoin / Q000737:chemistry; D000327:Adsorption; D000438:Alcohols / Q000737:chemistry; D002849:Chromatography, Gas; D014644:Genetic Variation; D023281:Genomics; D013058:Mass Spectrometry; D055432:Metabolomics; D008957:Models, Genetic; D005810:Multigene Family; D018034:Olfactory Receptor Neurons / Q000378:metabolism; D000439:Pentanols / Q000737:chemistry; D010641:Phenotype; D010626:Phenylethyl Alcohol / Q000737:chemistry; D010802:Phylogeny; D020641:Polymorphism, Single Nucleotide; D025341:Principal Component Analysis; D011336:Probability; D012441:Saccharomyces cerevisiae / Q000235:genetics* / Q000378:metabolism*; D015398:Signal Transduction
chemical_list: D000438:Alcohols; D000439:Pentanols; D000093:Acetoin; C029683:isopentyl alcohol; D010626:Phenylethyl Alcohol