Browsing by Subject "yeast"

Now showing 1 - 4 of 4
  • Thumbnail Image
    Item
    Antibiotic use is a short-term risk factor for symptomatic vulvovaginal candidiasis
    (2010-07-29) Semenkewitz, Kelly
    Antibiotic therapy is a short-term risk factor for vulvovaginal candidiasis both in first episodes and in recurrent infections. Additionally, increased duration of antibiotic use is directly correlated with an increased prevalence of Candida vaginal infection.
  • Thumbnail Image
    Item
    Development of two-color quantitative single-molecule localization microscopy in living yeast
    (2022-12) Mancebo Jr, Angel
    Single-molecule localization microscopy (SMLM) is a powerful technique that enables the observation of protein organization in living cells at a resolution well below the optical diffraction limit. Through the wide variety of specific labels that are available, it has become possible to use two-color SMLM to observe and quantify colocalization between two protein species. The information obtained from their colocalization can yield insights into their possible interaction as well as their relative enrichment. Identifying sites of interaction remains a challenge, in part because there are often large concentration ratios between interacting partners and few interactions occurring relative to the number of the more abundant species. The robust and genetically-manipulable budding yeast, Saccharomyces cerevisiae, with many genes and pathways homologous to those in mammals, serves as a powerful tool for expediting studies in eukaryotic cells. However, two-color SMLM has not been possible in living yeast. This is because the dyes that are used in mammalian cells for achieving a second color are actively exported by yeast. In this thesis I present work towards the development of two-color SMLM in living yeast. I show a simple approach for patterning of photoactivation light with sub-diffraction precision, which has the added benefit of reducing phototoxicity. This patterned photoactivation also enables diffusion contrast photoactivation localization microscopy (dcPALM), which exploits differences in mobility between proteins that are interacting or not interacting with a binding partner to reduce the non-interacting background. Progressing closer into two-color SMLM, I show a method for efficiently separating localizations based on cross-correlation between two channels, with an application to a mammalian system in which it was demonstrated that a critical number of a key protein in the initiation of autophagy needed to be present to initiate autophagy. Finally, I show for the first time two-color SMLM in living yeast — particularly with Janelia Fluor HaloTag dyes — and the characterization of a drug that facilitates the uptake of the dyes into yeast.
  • Thumbnail Image
    Item
    Genotype-by-environment interactions and causal gene fine-mapping for quantitative trait variation in yeast
    (2024-12) Avery, Randi
    Genetic variation among individuals influences many important traits, including common human disease. Quantitative trait locus (QTL) mapping in model organisms has revealed that most quantitative traits are affected by multiple QTLs throughout the genome, and are therefore “complex” traits. Complex traits also include those affected by genotype-by-environment interactions (GxE), where the effect of a genetic variant on a trait depends on the environment. GxE influences numerous organismal traits across eukaryotic life. However, we have a limited understanding of how GxE shapes the molecular processes that give rise to organismal traits. This work covers two main areas using the yeast Saccharomyces cerevisiae: GxE through QTL mapping for the trait of protein degradation and dissecting QTLs to gene-level resolution. We characterized how GxE shapes protein degradation, an essential molecular process that influences numerous aspects of cellular and organismal physiology. We characterized GxE in the activity of the ubiquitin-proteasome system (UPS), the primary protein degradation system in eukaryotes. By mapping genetic influences on the degradation of six substrates that engage multiple distinct UPS pathways across eight diverse environments, we discovered extensive GxE in the genetics of UPS activity. Hundreds of locus effects on UPS activity varied depending on the substrate, the environment, or both. Most of these cases corresponded to loci that were present in one environment but not another (“presence / absence” GxE), while a smaller number of loci had opposing effects in different environments (“sign change” GxE). The number of loci exhibiting GxE, their genomic location, and the type of GxE (presence / absence or sign change) varied across UPS substrates. Loci exhibiting GxE were clustered at genomic regions that contain core UPS genes and especially at regions containing variation that affects the expression of thousands of genes, suggesting indirect contributions to UPS activity. Our results reveal highly complex interactions at the level of substrates and environments in the genetics of protein degradation.Identifying the causal genes within QTLs (quantitative trait genes; QTGs) is challenging because most QTLs are wide and can contain dozens of genes. Experimental fine-mapping approaches typically test causality one gene at a time. This process is both laborious and potentially biased towards genes previously shown to affect the trait. To systematically identify QTGs with high-throughput, we applied the reciprocal heterozygosity (RH) test genome-wide using transposon mutagenesis for the model complex trait of growth in a hybrid of two genetically different S. cerevisiae strains. We used Illumina sequencing of transposon insertion sites to count insertions at each open reading frame (ORF). Out of the 4,784 ORFs that carry DNA variants between the two parental strains of the hybrid, 4,440 contained at least one insertion, with 4,260 ORFs containing at least one insertion in both alleles. Using a custom computational pipeline and linear modeling, we identified 265 genes with at least a nominally significant (p < 0.05) allelic effect on growth, however, experimental validation did not recapitulate the results of the scan. Here, I discuss multiple possibilities for this result and propose improvements to the approach. Directly mapping QTGs will aid in understanding how genetic variation affects important cellular traits, such as growth, and can be readily applied to other phenotypes. This work contributes valuable insights to the field complex trait genetics by elucidating the genetic architecture of UPS activity in yeast. Furthermore, an approach to directly map QTGs will be fundamental in understanding causal mechanisms behind complex traits, and I have laid the groundwork to apply this approach to a hybrid of two S. cerevisiae strains.
  • Thumbnail Image
    Item
    Pleiotropy and epistasis in trans-acting expression quantitative loci hotspots
    (2023-11) Van Dyke, Krisna
    Differences in non-coding regions of genomes explain the majority of heritable differences between individuals such as disease heritability. These non-coding differences are thought to largely act by altering gene expression, positioning regulatory variation as a key bridge between DNA variation and differences in traits. Expression quantitative trait loci (eQTLs) are regions of the genome containing one or more variants that alter the expression of a gene. In a cross between two strains of Saccharomyces cerevisiae, most heritable variation in gene expression acted in trans, with 90% of these trans-eQTLs overlapping only 102 “hotspot” loci. The large amount of heritable variation in gene expression that hotspots account for, and their discovery across the tree of life suggest they are a critical and ubiquitous feature of genome architecture. Classifying the structure of genetic variation underlying hotspots and learning what mechanisms allow hotspots to affect such large numbers of genes is critical to understanding how genetic variation gives rise to phenotypic variation. The following chapters describe a dissection of the variation underlying a hotspot and the uncovering of a new framework for how hotspots affect such numerous genes. Chapter II details how hotspots can co-opt the cellular mechanisms that cause adjacent genes to be coexpressed to extend their effect in cis. Chapter III dissects a hotspot with a complex epistatic basis to demonstrate how variants and groups of variants within a gene can interact to have wide-reaching impacts on the expression of many genes.