Evidence map›Paper›PMID 30852250›Full record

ArticleCell systems2019

Divergent Aging of Isogenic Yeast Cells Revealed through Single-Cell Phenotypic Dynamics.

Meng Jin, Yang Li, Richard O'Laughlin, Philip Bittihn, Lorraine Pillus, Lev S Tsimring, Jeff Hasty, Nan Hao

Open access · bronzeAbstract read
In one paragraph

Article in Cell systems, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers.

0numbers the graph read from it
0cells of the map it votes in
38citing papers in PubMed
3.1field-weighted citation impact, top 8% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

38 citing papers in PubMed, 65 citations in OpenAlex.

  1. Article
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  3. Single-cell analyses identify independent aging processes that compete to determine cellular fate in budding yeast.Proceedings of the National Academy of Sciences of the United States of America · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 1 institution in 1 country.

Meng JinBioCircuits Institute, University of California, San Diego, La Jolla, San Diego, CA 92093, USA.
Yang LiSection of Molecular Biology, Division of Biological Sciences, University of California, San Diego, La Jolla, San Diego, CA 92093, USA.
Richard O'LaughlinDepartment of Bioengineering, University of California, San Diego, La Jolla, San Diego, CA 92093, USA.
Philip BittihnBioCircuits Institute, University of California, San Diego, La Jolla, San Diego, CA 92093, USA.
Lorraine PillusSection of Molecular Biology, Division of Biological Sciences, University of California, San Diego, La Jolla, San Diego, CA 92093, USA; UCSD Moores Cancer Center, University of California, San Diego, La Jolla, San Diego, CA 92093, USA.
Lev S TsimringBioCircuits Institute, University of California, San Diego, La Jolla, San Diego, CA 92093, USA. Electronic address: ltsimring@ucsd.edu.
Jeff HastyBioCircuits Institute, University of California, San Diego, La Jolla, San Diego, CA 92093, USA; Section of Molecular Biology, Division of Biological Sciences, University of California, San Diego, La Jolla, San Diego, CA 92093, USA; Department of Bioengineering, University of California, San Diego, La Jolla, San Diego, CA 92093, USA. Electronic address: jhasty@eng.ucsd.edu.
Nan HaoBioCircuits Institute, University of California, San Diego, La Jolla, San Diego, CA 92093, USA; Section of Molecular Biology, Division of Biological Sciences, University of California, San Diego, La Jolla, San Diego, CA 92093, USA. Electronic address: nhao@ucsd.edu.
University of California, San Diego · US

Funding

SYNTHETIC SYSTEMSP50GM085764 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI JEPSEN, KRISTEN LYNN · 2010 to 2018
$23.3M
Engineered Gene Circuits for Basic Science and BiotechnologyR01GM069811 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI HASTY, JEFF M, TSIMRING, LEV S · 2004 to 2025
$13.6M
Network-Driven Dynamics of Replicative AgingR01AG056440 · NIA · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI JEFF M HASTY, Nan Hao · 2017 to 2026
$5.6M
NIA NIH HHS R01 AG056440NIGMS NIH HHS P50 GM085764NIGMS NIH HHS R01 GM069811
6 · The paper itself

Abstract

Although genetic mutations that alter organisms' average lifespans have been identified in aging research, our understanding of the dynamic changes during aging remains limited. Here, we integrate single-cell imaging, microfluidics, and computational modeling to investigate phenotypic divergence and cellular heterogeneity during replicative aging of single S. cerevisiae cells. Specifically, we find that isogenic cells diverge early in life toward one of two aging paths, which are characterized by distinct age-associated phenotypes. We captured the dynamics of single cells along the paths with a stochastic discrete-state model, which accurately predicts both the measured heterogeneity and the lifespan of cells on each path within a cell population. Our analysis suggests that genetic and environmental factors influence both a cell's choice of paths and the kinetics of paths themselves. Given that these factors are highly conserved throughout eukaryotes, divergent aging might represent a general scheme in cellular aging of other organisms.

Indexed as

Cellular SenescenceComputer SimulationDNA ReplicationModels, BiologicalComputational BiologyMicrofluidicsSaccharomyces cerevisiaeSingle-Cell Analysiscaloric restrictioncell fate decisioncellular agingcomputational modelingdynamicsmicrofluidicssingle-cell analysissirtuinsstochastic simulationstime-lapse microscopy

Identifiers

PMID30852250
PMCPMC6514117
OpenAlexW2921688087

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.