ABSTRACT
Caffeine is a natural compound that inhibits the major cellular signaling regulator TOR, leading to widespread effects including growth inhibition. S. cerevisiae yeast can adapt to tolerate high concentrations of caffeine in coffee and cacao fermentations and in experimental systems. While many factors affecting caffeine tolerance and TOR signaling have been identified, further characterization of their interactions and regulation remain to be studied. We used experimental evolution of S. cerevisiae to study the genetic contributions to caffeine tolerance in yeast, through a collaboration between high school students evolving yeast populations coupled with further research exploration in university labs. We identified multiple evolved yeast populations with mutations in PDR1 and PDR5, which contribute to multidrug resistance, and showed that gain-of-function mutations in multidrug resistance family transcription factors Pdr1, Pdr3, and Yrr1 differentially contribute to caffeine tolerance. We also identified loss-of-function mutations in TOR effectors Sit4, Sky1, and Tip41, and show that these mutations contribute to caffeine tolerance. These findings support the importance of both the multidrug resistance family and TOR signaling in caffeine tolerance, and can inform future exploration of networks affected by caffeine and other TOR inhibitors in model systems and industrial applications.
ABSTRACT
URA3 is frequently used in the yeast community as the mutation target for 5-fluoroorotic acid (5-FOA) resistance. We identified a novel class of ura6 mutants that can grow in the presence of 5-FOA. Unlike ura3 mutants, ura6 mutants remain prototrophic and grow in the absence of uracil. In addition to 5-FOA resistance, we found that mutations to URA6 also confer resistance to 5-fluorocytosine (5-FC) and 5-fluorouracil (5-FU). In total, we identified 50 unique missense mutations across 32 residues of URA6. We found that 28 out of the 32 affected residues are located in regions conserved between Saccharomyces cerevisiae and three clinically relevant pathogenic fungi. These findings suggest that mutations to URA6 present a second target for mutation screens utilizing 5-FOA as a selection marker as well as a potential mode of resistance to the antifungal therapeutic 5-FC.
ABSTRACT
Caffeine is a natural compound that inhibits the major cellular signaling regulator TOR, leading to widespread effects including growth inhibition. S. cerevisiae yeast can adapt to tolerate high concentrations of caffeine in coffee and cacao fermentations and in experimental systems. While many factors affecting caffeine tolerance and TOR signaling have been identified, further characterization of their interactions and regulation remain to be studied. We used experimental evolution of S. cerevisiae to study the genetic contributions to caffeine tolerance in yeast, through a collaboration between high school students evolving yeast populations coupled with further research exploration in university labs. We identified multiple evolved yeast populations with mutations in PDR1 and PDR5, which contribute to multidrug resistance, and showed that gain-of-function mutations in multidrug resistance family transcription factors PDR1, PDR3, and YRR1 differentially contribute to caffeine tolerance. We also identified loss-of-function mutations in TOR effectors SIT4, SKY1, and TIP41, and show that these mutations contribute to caffeine tolerance. These findings support the importance of both the multidrug resistance family and TOR signaling in caffeine tolerance, and can inform future exploration of networks affected by caffeine and other TOR inhibitors in model systems and industrial applications.
ABSTRACT
MOTIVATION: Long-read sequencing technologies, an attractive solution for many applications, often suffer from higher error rates. Alignment of multiple reads can improve base-calling accuracy, but some applications, e.g. sequencing mutagenized libraries where multiple distinct clones differ by one or few variants, require the use of barcodes or unique molecular identifiers. Unfortunately, sequencing errors can interfere with correct barcode identification, and a given barcode sequence may be linked to multiple independent clones within a given library. RESULTS: Here we focus on the target application of sequencing mutagenized libraries in the context of multiplexed assays of variant effects (MAVEs). MAVEs are increasingly used to create comprehensive genotype-phenotype maps that can aid clinical variant interpretation. Many MAVE methods use long-read sequencing of barcoded mutant libraries for accurate association of barcode with genotype. Existing long-read sequencing pipelines do not account for inaccurate sequencing or nonunique barcodes. Here, we describe Pacybara, which handles these issues by clustering long reads based on the similarities of (error-prone) barcodes while also detecting barcodes that have been associated with multiple genotypes. Pacybara also detects recombinant (chimeric) clones and reduces false positive indel calls. In three example applications, we show that Pacybara identifies and correctly resolves these issues. AVAILABILITY AND IMPLEMENTATION: Pacybara, freely available at https://github.com/rothlab/pacybara, is implemented using R, Python, and bash for Linux. It runs on GNU/Linux HPC clusters via Slurm, PBS, or GridEngine schedulers. A single-machine simplex version is also available.
Subject(s)
High-Throughput Nucleotide Sequencing , Software , Sequence Analysis, DNA/methods , High-Throughput Nucleotide Sequencing/methods , Gene Library , Genotype , Cluster AnalysisABSTRACT
Inherited and germ-line de novo copy number variants (CNVs) are increasingly found to be correlated with human developmental and cancerous phenotypes. Several models for template switching during replication have been proposed to explain the generation of these gross chromosomal rearrangements. We proposed a model of template switching (ODIRA-origin dependent inverted repeat amplification) in which simultaneous ligation of the leading and lagging strands at diverging replication forks could generate segmental inverted triplications through an extrachromosomal inverted circular intermediate. Here, we created a genetic assay using split-ura3 cassettes to trap the proposed inverted intermediate. However, instead of recovering circular inverted intermediates, we found inverted linear chromosomal fragments ending in native telomeres-suggesting that a template switch had occurred at the centromere-proximal fork of a replication bubble. As telomeric inverted hairpin fragments can also be created through double strand breaks we tested whether replication errors or repair of double stranded DNA breaks were the most likely initiating event. The results from CRISPR/Cas9 cleavage experiments and growth in the replication inhibitor hydroxyurea indicate that it is a replication error, not a double stranded break that creates the inverted junctions. Since inverted amplicons of the SUL1 gene occur during long-term growth in sulfate-limited chemostats, we sequenced evolved populations to look for evidence of linear intermediates formed by an error in replication. All of the data are compatible with a two-step version of the ODIRA model in which sequential template switching at short inverted repeats between the leading and lagging strands at a replication fork, followed by integration via homologous recombination, generates inverted interstitial triplications.
Subject(s)
DNA Copy Number Variations , DNA Replication , Humans , DNA Replication/genetics , DNA Copy Number Variations/genetics , Chromosome Aberrations , DNA Breaks, Double-Stranded , DNAABSTRACT
With the release of the telomere-to-telomere human genome sequence and the availability of both long-read sequencing and optical genome mapping techniques, the identification of copy number variants (CNVs) and other structural variants is providing new insights into human genetic disease. Different mechanisms have been proposed to account for the novel junctions in these complex architectures, including aberrant forms of DNA replication, non-allelic homologous recombination, and various pathways that repair DNA breaks. Here, we have focused on a set of structural variants that include an inverted segment and propose that they share a common initiating event: an inverted triplication with long, unstable palindromic junctions. The secondary rearrangement of these palindromes gives rise to the various forms of inverted structural variants. We postulate that this same mechanism (ODIRA: origin-dependent inverted-repeat amplification) that creates the inverted CNVs in inherited syndromes also generates the palindromes found in cancers.
Subject(s)
DNA Copy Number Variations , Homologous Recombination , Humans , DNA Copy Number Variations/genetics , Base Sequence , DNA Replication/genetics , Inverted Repeat SequencesABSTRACT
The resources for carrying out and analyzing microbial evolution experiments have become more accessible, making it possible to expand these studies beyond the research laboratory and into the classroom. We developed five connected, standards-aligned yeast evolution laboratory modules, called "yEvo," for high school students. The modules enable students to take agency in answering open-ended research questions. In Module 1, students evolve baker's yeast to tolerate an antifungal drug, and in subsequent modules, investigate how evolved yeasts adapted to this stressful condition at both the phenotype and genotype levels. We used pre- and post-surveys from 72 students at two different schools and post-interviews with students and teachers to assess our program goals and guide module improvement over 3 years. We measured changes in student conceptions, confidence in scientific practices, and interest in STEM careers. Students who participated in yEvo showed improvements in understanding of activity-specific concepts and reported increased confidence in designing a valid biology experiment. Student experimental data replicated literature findings and has led to new insights into antifungal resistance. The modules and provided materials, alongside "proof of concept" evaluation metrics, will serve as a model for other university researchers and K - 16 classrooms interested in engaging in open-ended research questions using yeast as a model system.
ABSTRACT
Assessing the complexity and expressivity of traits at the species level is an essential first step to better dissect the genotype-phenotype relationship. As trait complexity behaves dynamically, the classic dichotomy between monogenic and complex traits is too simplistic. However, no systematic assessment of this complexity spectrum has been carried out on a population scale to date. In this context, we generated a large diallel hybrid panel composed of 190 unique hybrids coming from 20 natural isolates representative of the S. cerevisiae genetic diversity. For each of these hybrids, a large progeny of 160 individuals was obtained, leading to a total of 30,400 offspring individuals. Their mitotic growth was evaluated on 38 conditions inducing various cellular stresses. We developed a classification algorithm to analyze the phenotypic distributions of offspring and assess the trait complexity. We clearly found that traits are mainly complex at the population level. On average, we found that 91.2% of cross/trait combinations exhibit high complexity, while monogenic and oligogenic cases accounted for only 4.1% and 4.7%, respectively. However, the complexity spectrum is very dynamic, trait specific and tightly related to genetic backgrounds. Overall, our study provided greater insight into trait complexity as well as the underlying genetic basis of its spectrum in a natural population.
Subject(s)
Quantitative Trait Loci , Saccharomyces cerevisiae , Humans , Saccharomyces cerevisiae/genetics , Quantitative Trait Loci/genetics , Genetic Variation , PhenotypeABSTRACT
Studying the genetic and molecular characteristics of brewing yeast strains is crucial for understanding their domestication history and adaptations accumulated over time in fermentation environments, and for guiding optimizations to the brewing process itself. Saccharomyces cerevisiae (brewing yeast) is among the most profiled organisms on the planet, yet the temporal molecular changes that underlie industrial fermentation and beer brewing remain understudied. Here, we characterized the genomic makeup of a Saccharomyces cerevisiae ale yeast widely used in the production of Hefeweizen beers, and applied shotgun mass spectrometry to systematically measure the proteomic changes throughout 2 fermentation cycles which were separated by 14 rounds of serial repitching. The resulting brewing yeast proteomics resource includes 64,740 protein abundance measurements. We found that this strain possesses typical genetic characteristics of Saccharomyces cerevisiae ale strains and displayed progressive shifts in molecular processes during fermentation based on protein abundance changes. We observed protein abundance differences between early fermentation batches compared to those separated by 14 rounds of serial repitching. The observed abundance differences occurred mainly in proteins involved in the metabolism of ergosterol and isobutyraldehyde. Our systematic profiling serves as a starting point for deeper characterization of how the yeast proteome changes during commercial fermentations and additionally serves as a resource to guide fermentation protocols, strain handling, and engineering practices in commercial brewing and fermentation environments. Finally, we created a web interface (https://brewing-yeast-proteomics.ccbb.utexas.edu/) to serve as a valuable resource for yeast geneticists, brewers, and biochemists to provide insights into the global trends underlying commercial beer production.
Subject(s)
Proteomics , Saccharomyces cerevisiae , Saccharomyces cerevisiae/genetics , Saccharomyces cerevisiae/metabolism , Fermentation , Fungal Proteins/genetics , Fungal Proteins/metabolism , Beer/analysisABSTRACT
Studying the genetic and molecular characteristics of brewing yeast strains is crucial for understanding their domestication history and adaptations accumulated over time in fermentation environments, and for guiding optimizations to the brewing process itself. Saccharomyces cerevisiae (brewing yeast) is amongst the most profiled organisms on the planet, yet the temporal molecular changes that underlie industrial fermentation and beer brewing remain understudied. Here, we characterized the genomic makeup of a Saccharomyces cerevisiae ale yeast widely used in the production of Hefeweizen beers, and applied shotgun mass spectrometry to systematically measure the proteomic changes throughout two fermentation cycles which were separated by 14 rounds of serial repitching. The resulting brewing yeast proteomics resource includes 64,740 protein abundance measurements. We found that this strain possesses typical genetic characteristics of Saccharomyces cerevisiae ale strains and displayed progressive shifts in molecular processes during fermentation based on protein abundance changes. We observed protein abundance differences between early fermentation batches compared to those separated by 14 rounds of serial repitching. The observed abundance differences occurred mainly in proteins involved in the metabolism of ergosterol and isobutyraldehyde. Our systematic profiling serves as a starting point for deeper characterization of how the yeast proteome changes during commercial fermentations and additionally serves as a resource to guide fermentation protocols, strain handling, and engineering practices in commercial brewing and fermentation environments. Finally, we created a web interface (https://brewing-yeast-proteomics.ccbb.utexas.edu/) to serve as a valuable resource for yeast geneticists, brewers, and biochemists to provide insights into the global trends underlying commercial beer production.
ABSTRACT
Whole-chromosome aneuploidy and large segmental amplifications can have devastating effects in multicellular organisms, from developmental disorders and miscarriage to cancer. Aneuploidy in single-celled organisms such as yeast also results in proliferative defects and reduced viability. Yet, paradoxically, CNVs are routinely observed in laboratory evolution experiments with microbes grown in stressful conditions. The defects associated with aneuploidy are often attributed to the imbalance of many differentially expressed genes on the affected chromosomes, with many genes each contributing incremental effects. An alternate hypothesis is that a small number of individual genes are large effect 'drivers' of these fitness changes when present in an altered copy number. To test these two views, we have employed a collection of strains bearing large chromosomal amplifications that we previously assayed in nutrient-limited chemostat competitions. In this study, we focus on conditions known to be poorly tolerated by aneuploid yeast-high temperature, treatment with the Hsp90 inhibitor radicicol, and growth in extended stationary phase. To identify potential genes with a large impact on fitness, we fit a piecewise constant model to fitness data across chromosome arms, filtering breakpoints in this model by magnitude to focus on regions with a large impact on fitness in each condition. While fitness generally decreased as the length of the amplification increased, we were able to identify 91 candidate regions that disproportionately impacted fitness when amplified. Consistent with our previous work with this strain collection, nearly all candidate regions were condition specific, with only five regions impacting fitness in multiple conditions.
ABSTRACT
yEvo is a curriculum for high school students centered around evolution experiments in S. cerevisiae . To adapt the curriculum for remote instruction, we created a new protocol to evolve non-engineered yeast in the presence of caffeine. Evolved strains had increased caffeine tolerance and distinct colony morphologies. Many possessed copy number variations, transposon insertions, and mutations affecting genes with known relationships to caffeine and TOR signaling - which is inhibited by caffeine - and in other genes not previously connected with caffeine. This demonstrates that our accessible, at-home protocol is sufficient to permit novel insights into caffeine tolerance.
ABSTRACT
Long read sequencing technologies, an attractive solution for many applications, often suffer from higher error rates. Alignment of multiple reads can improve base-calling accuracy, but some applications, e.g. sequencing mutagenized libraries where multiple distinct clones differ by one or few variants, require the use of barcodes or unique molecular identifiers. Unfortunately, sequencing errors can interfere with correct barcode identification, and a given barcode sequence may be linked to multiple independent clones within a given library. Here we focus on the target application of sequencing mutagenized libraries in the context of multiplexed assays of variant effects (MAVEs). MAVEs are increasingly used to create comprehensive genotype-phenotype maps that can aid clinical variant interpretation. Many MAVE methods use long-read sequencing of barcoded mutant libraries for accurate association of barcode with genotype. Existing long-read sequencing pipelines do not account for inaccurate sequencing or non-unique barcodes. Here, we describe Pacybara, which handles these issues by clustering long reads based on the similarities of (error-prone) barcodes while also detecting barcodes that have been associated with multiple genotypes. Pacybara also detects recombinant (chimeric) clones and reduces false positive indel calls. In three example applications, we show that Pacybara identifies and correctly resolves these issues.
ABSTRACT
Evolution is driven by the accumulation of competing mutations that influence survival. A broad form of genetic variation is the amplification or deletion of DNA (≥50 bp) referred to as copy number variation (CNV). In humans, CNV may be inconsequential, contribute to minor phenotypic differences, or cause conditions such as birth defects, neurodevelopmental disorders, and cancers. To identify mechanisms that drive CNV, we monitored the experimental evolution of Saccharomyces cerevisiae populations grown under sulfate-limiting conditions. Cells with increased copy number of the gene SUL1, which encodes a primary sulfate transporter, exhibit a fitness advantage. Previously, we reported interstitial inverted triplications of SUL1 as the dominant rearrangement in a haploid population. Here, in a diploid population, we find instead that small linear fragments containing SUL1 form and are sustained over several generations. Many of the linear fragments are stabilized by de novo telomere addition within a telomere-like sequence near SUL1 (within the SNF5 gene). Using an assay that monitors telomerase action following an induced chromosome break, we show that this region acts as a hotspot of de novo telomere addition and that required sequences map to a region of <250 base pairs. Consistent with previous work showing that association of the telomere-binding protein Cdc13 with internal sequences stimulates telomerase recruitment, mutation of a four-nucleotide motif predicted to associate with Cdc13 abolishes de novo telomere addition. Our study suggests that internal telomere-like sequences that stimulate de novo telomere addition can contribute to adaptation by promoting genomic plasticity.
Subject(s)
Saccharomyces cerevisiae Proteins , Telomerase , Humans , Saccharomyces cerevisiae/genetics , Saccharomyces cerevisiae/metabolism , Saccharomyces cerevisiae Proteins/genetics , Saccharomyces cerevisiae Proteins/metabolism , Telomerase/genetics , Telomerase/metabolism , Sulfates/metabolism , DNA Copy Number Variations , Telomere-Binding Proteins/genetics , Telomere/genetics , Telomere/metabolism , Sulfate Transporters/genetics , Sulfate Transporters/metabolismABSTRACT
yEvo is a curriculum for high school students centered around evolution experiments in S. cerevisiae . To adapt the curriculum for remote instruction, we created a new protocol to evolve non-GMO yeast in the presence of caffeine. Evolved strains had increased caffeine tolerance and distinct colony morphologies. Many possessed copy number variations, transposon insertions, and mutations affecting genes with known relationships to caffeine and TOR signaling - which is inhibited by caffeine - and in other genes not previously connected with caffeine. This demonstrates that our accessible, at-home protocol is sufficient to permit novel insights into caffeine tolerance.
ABSTRACT
Glucose-6-phosphate dehydrogenase (G6PD) deficiency affects over 500 million individuals who can experience anemia in response to oxidative stressors such as certain foods and drugs. Recently, the World Health Organization (WHO) called for revisiting G6PD variant classification as a priority to implement genetic medicine in low- and middle-income countries. Toward this goal, we sought to collect reports of G6PD variants and provide interpretations. We identified 1,341 G6PD variants in population and clinical databases. Using the ACMG standards and guidelines for the interpretation of sequence variants, we provided interpretations for 268 variants, including 186 variants that were not reported or of uncertain significance in ClinVar, bringing the total number of variants with non-conflicting interpretations to 400. For 414 variants with functional or clinical data, we analyzed associations between activity, stability, and current classification systems, including the new 2022 WHO classification. We corroborated known challenges with classification systems, including phenotypic variation, emphasizing the importance of comparing variant effects across individuals and studies. Biobank data made available by All of Us illustrate the benefit of large-scale sequencing and phenotyping by adding additional support connecting variants to G6PD-deficient anemia. By leveraging available data and interpretation guidelines, we created a repository for information on G6PD variants and nearly doubled the number of variants with clinical interpretations. These tools enable better interpretation of G6PD variants for the implementation of genetic medicine.
Subject(s)
Glucosephosphate Dehydrogenase Deficiency , Population Health , Humans , Glucosephosphate Dehydrogenase/genetics , Glucosephosphate Dehydrogenase Deficiency/genetics , Glucosephosphate Dehydrogenase Deficiency/epidemiology , Biological Variation, Population , CatalogingABSTRACT
Antifungal resistance in pathogenic fungi is a growing global health concern. Nonpathogenic laboratory strains of Saccharomyces cerevisiae are an important model for studying mechanisms of antifungal resistance that are relevant to understanding the same processes in pathogenic fungi. We have developed a series of laboratory modules in which high school students used experimental evolution to study antifungal resistance by isolating azole-resistant S. cerevisiae mutants and examining the genetic basis of resistance. We have sequenced 99 clones from these experiments and found that all possessed mutations previously shown to impact azole resistance, validating our approach. We additionally found recurrent mutations in an mRNA degradation pathway and an uncharacterized mitochondrial protein (Csf1) that have possible mechanistic connections to azole resistance. The scale of replication in this initiative allowed us to identify candidate epistatic interactions, as evidenced by pairs of mutations that occur in the same clone more frequently than expected by chance (positive epistasis) or less frequently (negative epistasis). We validated one of these pairs, a negative epistatic interaction between gain-of-function mutations in the multidrug resistance transcription factors Pdr1 and Pdr3. This high school-university collaboration can serve as a model for involving members of the broader public in the scientific process to make meaningful discoveries in biomedical research.
Subject(s)
Clotrimazole , Drug Resistance, Fungal , Saccharomyces cerevisiae Proteins , Saccharomyces cerevisiae , Antifungal Agents/pharmacology , Clotrimazole/pharmacology , DNA-Binding Proteins/genetics , Drug Resistance, Fungal/genetics , Mutation , Saccharomyces cerevisiae/genetics , Saccharomyces cerevisiae/metabolism , Saccharomyces cerevisiae Proteins/genetics , Saccharomyces cerevisiae Proteins/metabolism , Transcription Factors/geneticsABSTRACT
Expansion of sequencing efforts to include thousands of genomes is providing a fundamental resource for determining the genetic diversity that exists in a population. Now, high-throughput approaches are necessary to begin to understand the role these genotypic changes play in affecting phenotypic variation. Saccharomyces cerevisiae maintains its position as an excellent model system to determine the function of unknown variants with its exceptional genetic diversity, phenotypic diversity, and reliable genetic manipulation tools. Here, we review strategies and techniques developed in yeast that scale classic approaches of assessing variant function. These approaches improve our ability to better map quantitative trait loci at a higher resolution, even for rare variants, and are already providing greater insight into the role that different types of mutations play in phenotypic variation and evolution not just in yeast but across taxa.
Subject(s)
Saccharomyces cerevisiae Proteins , Saccharomyces cerevisiae , Chromosome Mapping , Genetic Variation/genetics , Phenotype , Quantitative Trait Loci/genetics , Saccharomyces cerevisiae/genetics , Saccharomyces cerevisiae Proteins/geneticsABSTRACT
Understanding the generation of mutations is fundamental to understanding evolution and genetic disease; however, the rarity of such events makes experimentally identifying them difficult. Mutation accumulation (MA) methods have been widely used. MA lines require serial bottlenecks to fix de novo mutations, followed by whole-genome sequencing. While powerful, this method is not suitable for exploring mutation variation among different genotypes due to its poor scalability with cost and labor. Alternatively, fluctuation assays estimate mutation rate in microorganisms by utilizing a reporter gene, in which Loss-of-function (LOF) mutations can be selected for using drugs toxic to cells containing the WT allele. Traditional fluctuation assays can estimate mutation rates but not their base change compositions. Here, we describe a new protocol that adapts traditional fluctuation assay using CAN1 reporter gene in Saccharomyces cerevisiae , followed by pooled sequencing methods, to identify both the rate and spectra of mutations in different strain backgrounds.