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Geck RC, Moresi NG, Anderson LM, Brewer R, Renz TR, Taylor MB, Dunham MJ. Experimental evolution of Saccharomyces cerevisiae for caffeine tolerance alters multidrug resistance and target of rapamycin signaling pathways. G3 (BETHESDA, MD.) 2024; 14:jkae148. [PMID: 38989875 PMCID: PMC11373655 DOI: 10.1093/g3journal/jkae148] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/28/2024] [Revised: 06/29/2024] [Accepted: 07/01/2024] [Indexed: 07/12/2024]
Abstract
Caffeine is a natural compound that inhibits the major cellular signaling regulator target of rapamycin (TOR), leading to widespread effects including growth inhibition. Saccharomyces 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 showed 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.
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Affiliation(s)
- Renee C Geck
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Naomi G Moresi
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Leah M Anderson
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | | | | | | | - Maitreya J Dunham
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
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Armstrong JO, Jiang P, Tsai S, Phan MMN, Harris K, Dunham MJ. URA6 mutations provide an alternative mechanism for 5-FOA resistance in Saccharomyces cerevisiae. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.03.597250. [PMID: 38895202 PMCID: PMC11185726 DOI: 10.1101/2024.06.03.597250] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/21/2024]
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.
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Affiliation(s)
| | - Pengyao Jiang
- Department of Genome Sciences, University of Washington
- Center for Mechanisms of Evolution, Biodesign Institute, School of Life Sciences, Arizona State University
| | - Skyler Tsai
- Department of Genome Sciences, University of Washington
| | | | - Kelley Harris
- Department of Genome Sciences, University of Washington
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Geck RC, Moresi NG, Anderson LM, Brewer R, Renz TR, Taylor MB, Dunham MJ. Experimental evolution of S. cerevisiae for caffeine tolerance alters multidrug resistance and TOR signaling pathways. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.28.591555. [PMID: 38746122 PMCID: PMC11092465 DOI: 10.1101/2024.04.28.591555] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/16/2024]
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.
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Affiliation(s)
- Renee C Geck
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Naomi G Moresi
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Leah M Anderson
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | | | | | - M Bryce Taylor
- Program in Biology, Loras College, Dubuque, IA 52001, USA
| | - Maitreya J Dunham
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
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Taylor MB, Warwick AR, Skophammer R, Boyer JM, Geck RC, Gunkelman K, Walson M, Rowley PA, Dunham MJ. yEvo: A modular eukaryotic genetics and evolution research experience for high school students. Ecol Evol 2024; 14:e10811. [PMID: 38192907 PMCID: PMC10771926 DOI: 10.1002/ece3.10811] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2022] [Accepted: 11/26/2023] [Indexed: 01/10/2024] Open
Abstract
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.
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Affiliation(s)
- M. Bryce Taylor
- Department of Genome SciencesUniversity of WashingtonSeattleWashingtonUSA
- Program in BiologyLoras CollegeDubuqueIowaUSA
| | - Alexa R. Warwick
- Department of Fisheries and WildlifeMichigan State UniversityEast LansingMichiganUSA
| | | | | | - Renee C. Geck
- Department of Genome SciencesUniversity of WashingtonSeattleWashingtonUSA
| | - Kristin Gunkelman
- Department of Teacher EducationMichigan State UniversityEast LansingMichiganUSA
| | - Margaux Walson
- Department of Genome SciencesUniversity of WashingtonSeattleWashingtonUSA
| | - Paul A. Rowley
- Department of Biological SciencesUniversity of IdahoMoscowIdahoUSA
| | - Maitreya J. Dunham
- Department of Genome SciencesUniversity of WashingtonSeattleWashingtonUSA
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Durand R, Jalbert-Ross J, Fijarczyk A, Dubé AK, Landry CR. Cross-feeding affects the target of resistance evolution to an antifungal drug. PLoS Genet 2023; 19:e1011002. [PMID: 37856537 PMCID: PMC10617708 DOI: 10.1371/journal.pgen.1011002] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2023] [Revised: 10/31/2023] [Accepted: 10/02/2023] [Indexed: 10/21/2023] Open
Abstract
Pathogenic fungi are a cause of growing concern. Developing an efficient and safe antifungal is challenging because of the similar biological properties of fungal and host cells. Consequently, there is an urgent need to better understand the mechanisms underlying antifungal resistance to prolong the efficacy of current molecules. A major step in this direction would be to be able to predict or even prevent the acquisition of resistance. We leverage the power of experimental evolution to quantify the diversity of paths to resistance to the antifungal 5-fluorocytosine (5-FC), commercially known as flucytosine. We generated hundreds of independent 5-FC resistant mutants derived from two genetic backgrounds from wild isolates of Saccharomyces cerevisiae. Through automated pin-spotting, whole-genome and amplicon sequencing, we identified the most likely causes of resistance for most strains. Approximately a third of all resistant mutants evolved resistance through a pleiotropic drug response, a potentially novel mechanism in response to 5-FC, marked by cross-resistance to fluconazole. These cross-resistant mutants are characterized by a loss of respiration and a strong tradeoff in drug-free media. For the majority of the remaining two thirds, resistance was acquired through loss-of-function mutations in FUR1, which encodes an important enzyme in the metabolism of 5-FC. We describe conditions in which mutations affecting this particular step of the metabolic pathway are favored over known resistance mutations affecting a step upstream, such as the well-known target cytosine deaminase encoded by FCY1. This observation suggests that ecological interactions may dictate the identity of resistance hotspots.
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Affiliation(s)
- Romain Durand
- Département de Biochimie, de Microbiologie et de Bio-informatique, Faculté des Sciences et de Génie, Université Laval, Canada
- Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval, Canada
- PROTEO, Le regroupement québécois de recherche sur la fonction, l’ingénierie et les applications des protéines, Université Laval, Québec, Canada
- Centre de Recherche sur les Données Massives (CRDM), Université Laval, Québec, Canada
- Département de Biologie, Faculté des Sciences et de Génie, Université Laval, Québec, Canada
| | - Jordan Jalbert-Ross
- Département de Biochimie, de Microbiologie et de Bio-informatique, Faculté des Sciences et de Génie, Université Laval, Canada
- Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval, Canada
- PROTEO, Le regroupement québécois de recherche sur la fonction, l’ingénierie et les applications des protéines, Université Laval, Québec, Canada
- Centre de Recherche sur les Données Massives (CRDM), Université Laval, Québec, Canada
| | - Anna Fijarczyk
- Département de Biochimie, de Microbiologie et de Bio-informatique, Faculté des Sciences et de Génie, Université Laval, Canada
- Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval, Canada
- PROTEO, Le regroupement québécois de recherche sur la fonction, l’ingénierie et les applications des protéines, Université Laval, Québec, Canada
- Centre de Recherche sur les Données Massives (CRDM), Université Laval, Québec, Canada
- Département de Biologie, Faculté des Sciences et de Génie, Université Laval, Québec, Canada
| | - Alexandre K. Dubé
- Département de Biochimie, de Microbiologie et de Bio-informatique, Faculté des Sciences et de Génie, Université Laval, Canada
- Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval, Canada
- PROTEO, Le regroupement québécois de recherche sur la fonction, l’ingénierie et les applications des protéines, Université Laval, Québec, Canada
- Centre de Recherche sur les Données Massives (CRDM), Université Laval, Québec, Canada
- Département de Biologie, Faculté des Sciences et de Génie, Université Laval, Québec, Canada
| | - Christian R. Landry
- Département de Biochimie, de Microbiologie et de Bio-informatique, Faculté des Sciences et de Génie, Université Laval, Canada
- Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval, Canada
- PROTEO, Le regroupement québécois de recherche sur la fonction, l’ingénierie et les applications des protéines, Université Laval, Québec, Canada
- Centre de Recherche sur les Données Massives (CRDM), Université Laval, Québec, Canada
- Département de Biologie, Faculté des Sciences et de Génie, Université Laval, Québec, Canada
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Chen J, Basting PJ, Han S, Garfinkel DJ, Bergman CM. Reproducible evaluation of transposable element detectors with McClintock 2 guides accurate inference of Ty insertion patterns in yeast. Mob DNA 2023; 14:8. [PMID: 37452430 PMCID: PMC10347736 DOI: 10.1186/s13100-023-00296-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2023] [Accepted: 06/09/2023] [Indexed: 07/18/2023] Open
Abstract
BACKGROUND Many computational methods have been developed to detect non-reference transposable element (TE) insertions using short-read whole genome sequencing data. The diversity and complexity of such methods often present challenges to new users seeking to reproducibly install, execute, or evaluate multiple TE insertion detectors. RESULTS We previously developed the McClintock meta-pipeline to facilitate the installation, execution, and evaluation of six first-generation short-read TE detectors. Here, we report a completely re-implemented version of McClintock written in Python using Snakemake and Conda that improves its installation, error handling, speed, stability, and extensibility. McClintock 2 now includes 12 short-read TE detectors, auxiliary pre-processing and analysis modules, interactive HTML reports, and a simulation framework to reproducibly evaluate the accuracy of component TE detectors. When applied to the model microbial eukaryote Saccharomyces cerevisiae, we find substantial variation in the ability of McClintock 2 components to identify the precise locations of non-reference TE insertions, with RelocaTE2 showing the highest recall and precision in simulated data. We find that RelocaTE2, TEMP, TEMP2 and TEBreak provide consistent estimates of [Formula: see text]50 non-reference TE insertions per strain and that Ty2 has the highest number of non-reference TE insertions in a species-wide panel of [Formula: see text]1000 yeast genomes. Finally, we show that best-in-class predictors for yeast applied to resequencing data have sufficient resolution to reveal a dyad pattern of integration in nucleosome-bound regions upstream of yeast tRNA genes for Ty1, Ty2, and Ty4, allowing us to extend knowledge about fine-scale target preferences revealed previously for experimentally-induced Ty1 insertions to spontaneous insertions for other copia-superfamily retrotransposons in yeast. CONCLUSION McClintock ( https://github.com/bergmanlab/mcclintock/ ) provides a user-friendly pipeline for the identification of TEs in short-read WGS data using multiple TE detectors, which should benefit researchers studying TE insertion variation in a wide range of different organisms. Application of the improved McClintock system to simulated and empirical yeast genome data reveals best-in-class methods and novel biological insights for one of the most widely-studied model eukaryotes and provides a paradigm for evaluating and selecting non-reference TE detectors in other species.
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Affiliation(s)
- Jingxuan Chen
- Institute of Bioinformatics, University of Georgia, Athens, GA USA
| | | | - Shunhua Han
- Institute of Bioinformatics, University of Georgia, Athens, GA USA
| | - David J. Garfinkel
- Department of Biochemistry and Molecular Biology, University of Georgia, Athens, GA USA
| | - Casey M. Bergman
- Institute of Bioinformatics, University of Georgia, Athens, GA USA
- Department of Genetics, University of Georgia, Athens, GA USA
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Moresi NG, Geck RC, Skophammer R, Godin D, Students YE, Taylor MB, Dunham MJ. Caffeine-tolerant mutations selected through an at-home yeast experimental evolution teaching lab. MICROPUBLICATION BIOLOGY 2023; 2023:10.17912/micropub.biology.000749. [PMID: 36855741 PMCID: PMC9968401 DOI: 10.17912/micropub.biology.000749] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Figures] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Revised: 02/02/2023] [Accepted: 01/01/1970] [Indexed: 03/02/2023]
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.
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Affiliation(s)
- Naomi G Moresi
- Genome Sciences, University of Washington, Seattle, Washington, United States
| | - Renee C Geck
- Genome Sciences, University of Washington, Seattle, Washington, United States
| | | | - Dennis Godin
- Genome Sciences, University of Washington, Seattle, Washington, United States
| | - yEvo Students
- Westridge School, Pasadena, California, United States
| | - M Bryce Taylor
- Program in Biology, Loras College, Dubuque, Iowa, United States
| | - Maitreya J Dunham
- Genome Sciences, University of Washington, Seattle, Washington, United States
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Moresi NG, Geck RC, Skophammer R, Godin D, Taylor MB, Dunham MJ. Caffeine-tolerant mutations selected through an at-home yeast experimental evolution teaching lab. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.01.17.524437. [PMID: 36712001 PMCID: PMC9882195 DOI: 10.1101/2023.01.17.524437] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
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-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.
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Affiliation(s)
- Naomi G. Moresi
- Department of Genome Sciences, University of Washington, Seattle, WA 98195
| | - Renee C. Geck
- Department of Genome Sciences, University of Washington, Seattle, WA 98195
| | | | - Dennis Godin
- Department of Genome Sciences, University of Washington, Seattle, WA 98195
| | | | | | - Maitreya J. Dunham
- Department of Genome Sciences, University of Washington, Seattle, WA 98195
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