ArticleiScience2018
Fundamental Characteristics of Single-Cell Aging in Diploid Yeast.
Article in iScience, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
18 citing papers in PubMed, 39 citations in OpenAlex.
- Equivalent Circuit Modeling and Analysis for Microfluidic Electrical Impedance Monitoring of Single-Cell Growth.Biosensors · 2025Article
- Capturing of extracellular vesicles derived from single cells ofLab on a chip · 2024Article
- Senescence in yeast is associated with amplified linear fragments of chromosome XII rather than ribosomal DNA circle accumulation.PLoS biology · 2023Article
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- A high-throughput microfluidic diploid yeast long-term culturing (DYLC) chip capable of bud reorientation and concerted daughter dissection for replicative lifespan determination.Journal of nanobiotechnology · 2022Article
- Article
- Modeling aging and its impact on cellular function and organismal behavior.Experimental gerontology · 2021Review
- A yeast-optimized single-cell transcriptomics platform elucidates how mycophenolic acid and guanine alter global mRNA levels.Communications biology · 2021Article
- Real-Time Monitoring of Dissection Events of Single Budding Yeast in a Microfluidic Cell-Culturing Device Integrated With Electrical Impedance Biosensor.Frontiers in bioengineering and biotechnology · 2021Article
- Variation, Variegation and Heritable Gene Repression inFrontiers in genetics · 2021Review
- Identifying longevity associated genes by integrating gene expression and curated annotations.PLoS computational biology · 2020Article
- Article
- Characterization of the impact of GMP/GDP synthesis inhibition on replicative lifespan extension in yeast.Current genetics · 2020Article
- Synergistic effects of repair, resilience and retention of damage determine the conditions for replicative ageing.Scientific reports · 2020Article
- Advances in quantitative biology methods for studying replicative aging inTranslational medicine of aging · 2020Article
- Proteostasis collapse, a hallmark of aging, hinders the chaperone-Start network and arrests cells in G1.eLife · 2019Article
- Stochastic modeling of aging cells reveals how damage accumulation, repair, and cell-division asymmetry affect clonal senescence and population fitness.BMC bioinformatics · 2019Article
- Recent advances in understanding the mechanisms determining longevity.F1000Research · 2019Review
Corrections and comments
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
Abstract
Single-cell-level experimentation can elucidate key biological insights about cellular aging that are masked in population-level studies. However, the extensive time requirement of tracking single cells has historically prevented their long-term longitudinal observation. Using a microfluidic device that automates microscopic monitoring of diploid Saccharomyces cerevisiae cells throughout their replicative lifespan, here we report the fundamental characteristics of single-cell aging for diploid yeast. We find that proteins with short versus long half-lives exhibit distinct dynamics as cells age and that the intercellular gene expression noise increases during aging, whereas the intracellular noise stays unchanged. A stochastic model provides quantitative mechanistic insights into the observed noise dynamics and sheds light on the age-dependent intracellular noise differences between diploid and haploid yeast. Our work elucidates how a set of canonical phenotypes dynamically change while the host cells are aging in real time, providing essential insights for a comprehensive understanding on and control of lifespan at the single-cell level.
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Registered trials
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.