ArticleExperimental gerontology2016
Gene-nutrient interaction markedly influences yeast chronological lifespan.
Article in Experimental gerontology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed, 30 citations in OpenAlex.
- Yeast Chronological Lifespan Model as a Tool for Screening Aging Interventions.International journal of molecular sciences · 2026Review
- The core genetic drivers of chronological aging in yeast are universal regulators of longevity.Microbial cell (Graz, Austria) · 2025Article
- The characteristics of differentiated yeast subpopulations depend on their lifestyle and available nutrients.Scientific reports · 2024Article
- Article
- Exploring the anti-aging potential of natural products and plant extracts in budding yeastF1000Research · 2023Review
- Genome-wide screens in yeast models towards understanding chronological lifespan regulation.Briefings in functional genomics · 2022Article
- Barcode sequencing and a high-throughput assay for chronological lifespan uncover ageing-associated genes in fission yeast.Microbial cell (Graz, Austria) · 2021Article
- Old yeasts, young beer-The industrial relevance of yeast chronological life span.Yeast (Chichester, England) · 2021Article
- High-resolution yeast quiescence profiling in human-like media reveals complex influences of auxotrophy and nutrient availability.GeroScience · 2021Article
- An Optimized Competitive-Aging Method Reveals Gene-Drug Interactions Underlying the Chronological Lifespan ofFrontiers in genetics · 2020Article
- A yeast phenomic model for the influence of Warburg metabolism on genetic buffering of doxorubicin.Cancer & metabolism · 2019Article
- Emerging Omics Approaches in Aging Research.Antioxidants & redox signaling · 2018Review
- Dietary restriction and lifespan: Lessons from invertebrate models.Ageing research reviews · 2017Review
- A cell-nonautonomous mechanism of yeast chronological aging regulated by caloric restriction and one-carbon metabolism.The Journal of biological chemistryArticle
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Authors and funding
5 authors at 2 institutions in 2 countries.
Funding
Abstract
purposeResearch into the genetic mechanisms of aging has expanded rapidly over the past two decades. This has in part been the result of the use of model organisms (particularly yeast, worms and flies) and high-throughput technologies, combined with a growing interest in aging research. Despite this progress, widespread consensus regarding the pathways that are fundamental to the modulation of cellular aging and lifespan for all organisms has been limited due to discrepancies between different studies. We have compared results from published genome-wide, chronological lifespan (CLS) screens of individual gene deletion strains in Saccharomyces cerevisiae in order to identify gene deletion strains with consistent influences on longevity as possible indicators of fundamental aging processes from this single-celled, eukaryotic model organism.
methodsThree previous reports have described genetic modifiers of chronological aging in the budding yeast (S. cerevisiae) using the yeast gene deletion strain collection. We performed a comparison among the data sets using correlation and decile distribution analysis to describe concordance between screens and identify strains that consistently increased or decreased CLS. We used gene enrichment analysis in an effort to understand the biology underlying genes identified in multiple studies. We attempted to replicate the different experimental conditions employed by the screens to identify potential sources of variability in CLS worth further investigating.
resultsAmong 3209 strains present in all three screens, nine deletions strains were in common in the longest-lived decile (2.80%) and thirteen were in common in the shortest-lived decile (4.05%) of all three screens. Similarly, pairwise overlap between screens was low. When the same comparison was extended to three deciles to include more mutants studied in common between the three screens, enrichment of cellular processes based on gene ontology analysis in the long-lived strains remained very limited. To test the hypothesis that different parental strain auxotrophic requirements or media formulations employed by the respective genome-wide screens might contribute to the lack of concordance, different CLS assay conditions were assessed in combination with strains having different ploidy and auxotrophic requirements (all relevant to differences in the way the three genome-wide CLS screens were performed). This limited but systematic analysis of CLS with respect to auxotrophy, ploidy, and media revealed several instances of gene-nutrient interaction.
conclusionsThere is surprisingly little overlap between the results of three independently performed genome-wide screens of CLS in S. cerevisiae. However, differences in strain genetic background (ploidy and specific auxotrophic requirements) were present, as well as different media and experimental conditions (e.g., aeration and pooled vs. individual culturing), which, along with stochastic effects such as genetic drift or selection of secondary mutations that suppress the loss of function from gene deletion, could in theory account for some of the lack of consensus between results. Considering the lack of overlap in CLS phenotypes among the set of genes reported by all three screens, and the results of a CLS experiment that systematically tested (incorporating extensive controls) for interactions between variables existing between the screens, we propose that discrepancies can be reconciled through deeper understanding of the influence of cell intrinsic factors such as auxotrophic requirements ploidy status, extrinsic factors such as media composition and aeration, as well as interactions that may occur between them, for example as a result of different pooling vs. individually aging cultures. Such factors may have a more significant impact on CLS outcomes than previously realized. Future studies that systematically account for these contextual factors, and can thus clarify the interactions between genetic and nutrient factors that alter CLS phenotypes, should aid more complete understanding of the underlying biology so that genetic principles of CLS in yeast can be extrapolated to differential cellular aging observed in animal models.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.