Literature DB >> 30852250

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

Meng Jin1, Yang Li2, Richard O'Laughlin3, Philip Bittihn1, Lorraine Pillus4, Lev S Tsimring5, Jeff Hasty6, Nan Hao7.   

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.
Copyright © 2019 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  caloric restriction; cell fate decision; cellular aging; computational modeling; dynamics; microfluidics; single-cell analysis; sirtuins; stochastic simulations; time-lapse microscopy

Mesh:

Year:  2019        PMID: 30852250      PMCID: PMC6514117          DOI: 10.1016/j.cels.2019.02.002

Source DB:  PubMed          Journal:  Cell Syst        ISSN: 2405-4712            Impact factor:   10.304


  35 in total

1.  Systematic analysis of asymmetric partitioning of yeast proteome between mother and daughter cells reveals "aging factors" and mechanism of lifespan asymmetry.

Authors:  Jing Yang; Mark A McCormick; Jiashun Zheng; Zhengwei Xie; Mitsuhiro Tsuchiya; Scott Tsuchiyama; Hana El-Samad; Qi Ouyang; Matt Kaeberlein; Brian K Kennedy; Hao Li
Journal:  Proc Natl Acad Sci U S A       Date:  2015-09-08       Impact factor: 11.205

2.  Regulation of yeast replicative life span by TOR and Sch9 in response to nutrients.

Authors:  Matt Kaeberlein; R Wilson Powers; Kristan K Steffen; Eric A Westman; Di Hu; Nick Dang; Emily O Kerr; Kathryn T Kirkland; Stanley Fields; Brian K Kennedy
Journal:  Science       Date:  2005-11-18       Impact factor: 47.728

3.  Multigenerational silencing dynamics control cell aging.

Authors:  Yang Li; Meng Jin; Richard O'Laughlin; Philip Bittihn; Lev S Tsimring; Lorraine Pillus; Jeff Hasty; Nan Hao
Journal:  Proc Natl Acad Sci U S A       Date:  2017-10-03       Impact factor: 11.205

Review 4.  Determining the Limitations and Benefits of Noise in Gene Regulation and Signal Transduction through Single Cell, Microscopy-Based Analysis.

Authors:  Marie D Harton; Eric Batchelor
Journal:  J Mol Biol       Date:  2017-03-11       Impact factor: 5.469

Review 5.  Extending healthy life span--from yeast to humans.

Authors:  Luigi Fontana; Linda Partridge; Valter D Longo
Journal:  Science       Date:  2010-04-16       Impact factor: 47.728

Review 6.  Microfluidic technologies for yeast replicative lifespan studies.

Authors:  Kenneth L Chen; Matthew M Crane; Matt Kaeberlein
Journal:  Mech Ageing Dev       Date:  2016-03-23       Impact factor: 5.432

Review 7.  Functional roles of pulsing in genetic circuits.

Authors:  Joe H Levine; Yihan Lin; Michael B Elowitz
Journal:  Science       Date:  2013-12-06       Impact factor: 47.728

8.  Geroscience: linking aging to chronic disease.

Authors:  Brian K Kennedy; Shelley L Berger; Anne Brunet; Judith Campisi; Ana Maria Cuervo; Elissa S Epel; Claudio Franceschi; Gordon J Lithgow; Richard I Morimoto; Jeffrey E Pessin; Thomas A Rando; Arlan Richardson; Eric E Schadt; Tony Wyss-Coray; Felipe Sierra
Journal:  Cell       Date:  2014-11-06       Impact factor: 41.582

9.  Role of SAGA in the asymmetric segregation of DNA circles during yeast ageing.

Authors:  Annina Denoth-Lippuner; Marek Konrad Krzyzanowski; Catherine Stober; Yves Barral
Journal:  Elife       Date:  2014-11-17       Impact factor: 8.140

10.  Yeast Sgf73/Ataxin-7 serves to anchor the deubiquitination module into both SAGA and Slik(SALSA) HAT complexes.

Authors:  Kenneth K Lee; Selene K Swanson; Laurence Florens; Michael P Washburn; Jerry L Workman
Journal:  Epigenetics Chromatin       Date:  2009-02-18       Impact factor: 4.954

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  17 in total

1.  A programmable fate decision landscape underlies single-cell aging in yeast.

Authors:  Yang Li; Yanfei Jiang; Julie Paxman; Richard O'Laughlin; Stephen Klepin; Yuelian Zhu; Lorraine Pillus; Lev S Tsimring; Jeff Hasty; Nan Hao
Journal:  Science       Date:  2020-07-17       Impact factor: 47.728

Review 2.  Modeling aging and its impact on cellular function and organismal behavior.

Authors:  Emerson Santiago; David F Moreno; Murat Acar
Journal:  Exp Gerontol       Date:  2021-09-26       Impact factor: 4.032

Review 3.  Single-cell image analysis to explore cell-to-cell heterogeneity in isogenic populations.

Authors:  Mojca Mattiazzi Usaj; Clarence Hue Lok Yeung; Helena Friesen; Charles Boone; Brenda J Andrews
Journal:  Cell Syst       Date:  2021-06-16       Impact factor: 11.091

4.  Searching for the Mechanisms of Mammalian Cellular Aging Through Underlying Gene Regulatory Networks.

Authors:  Wenbo Li; Lei Zhao; Jin Wang
Journal:  Front Genet       Date:  2020-06-30       Impact factor: 4.599

5.  An inexpensive microscopy system for microfluidic studies in budding yeast.

Authors:  Kenneth L Chen; Toby N Ven; Matthew M Crane; Dexter E Chen; Yen-Chi Feng; Nozomi Suzuki; Adam E Russell; Diogo de Moraes; Matt Kaeberlein
Journal:  Transl Med Aging       Date:  2019-06-07

6.  Scanning electron microscopy and machine learning reveal heterogeneity in capsular morphotypes of the human pathogen Cryptococcus spp.

Authors:  William Lopes; Giuliano N F Cruz; Marcio L Rodrigues; Mendeli H Vainstein; Livia Kmetzsch; Charley C Staats; Marilene H Vainstein; Augusto Schrank
Journal:  Sci Rep       Date:  2020-02-11       Impact factor: 4.379

Review 7.  Trajectories of Aging: How Systems Biology in Yeast Can Illuminate Mechanisms of Personalized Aging.

Authors:  Matthew M Crane; Kenneth L Chen; Ben W Blue; Matt Kaeberlein
Journal:  Proteomics       Date:  2019-11-04       Impact factor: 3.984

8.  Loss of vacuolar acidity results in iron-sulfur cluster defects and divergent homeostatic responses during aging in Saccharomyces cerevisiae.

Authors:  Kenneth L Chen; Toby N Ven; Matthew M Crane; Matthew L C Brunner; Adrian K Pun; Kathleen L Helget; Katherine Brower; Dexter E Chen; Ha Doan; Justin D Dillard-Telm; Ellen Huynh; Yen-Chi Feng; Zili Yan; Alexandra Golubeva; Roy A Hsu; Raheem Knight; Jessie Levin; Vesal Mobasher; Michael Muir; Victor Omokehinde; Corey Screws; Esin Tunali; Rachael K Tran; Luz Valdez; Edward Yang; Scott R Kennedy; Alan J Herr; Matt Kaeberlein; Brian M Wasko
Journal:  Geroscience       Date:  2020-01-23       Impact factor: 7.581

9.  A new mechanistic insight into fate decisions during yeast cell aging process.

Authors:  Morgan W Feng; Peter D Adams
Journal:  Mech Ageing Dev       Date:  2021-07-15       Impact factor: 5.498

10.  DNA damage checkpoint activation impairs chromatin homeostasis and promotes mitotic catastrophe during aging.

Authors:  Matthew M Crane; Adam E Russell; Brent J Schafer; Ben W Blue; Riley Whalen; Jared Almazan; Mung Gi Hong; Bao Nguyen; Joslyn E Goings; Kenneth L Chen; Ryan Kelly; Matt Kaeberlein
Journal:  Elife       Date:  2019-11-12       Impact factor: 8.140

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