Literature DB >> 31385433

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

Matthew M Crane1, Kenneth L Chen1,2,3, Ben W Blue1, Matt Kaeberlein1,2.   

Abstract

All organisms age, but the extent to which all organisms age the same way remains a fundamental unanswered question in biology. Across species, it is now clear that at least some aspects of aging are highly conserved and are perhaps universal, but other mechanisms of aging are private to individual species or sets of closely related species. Within the same species, however, it has generally been assumed that the molecular mechanisms of aging are largely invariant from one individual to the next. With the development of new tools for studying aging at the individual cell level in budding yeast, recent data has called this assumption into question. There is emerging evidence that individual yeast mother cells may undergo fundamentally different trajectories of aging. Individual trajectories of aging are difficult to study by traditional population level assays, but through the application of systems biology approaches combined with novel microfluidic technologies, it is now possible to observe and study these phenomena in real time. Understanding the spectrum of mechanisms that determine how different individuals age is a necessary step toward the goal of personalized geroscience, where healthy longevity is optimized for each individual.
© 2019 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Entities:  

Keywords:  Saccharomyces cerevisiae; budding yeast; longevity; replicative lifespan; single cells

Mesh:

Year:  2019        PMID: 31385433      PMCID: PMC7000301          DOI: 10.1002/pmic.201800420

Source DB:  PubMed          Journal:  Proteomics        ISSN: 1615-9853            Impact factor:   3.984


  86 in total

1.  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

2.  Changes in transcription and metabolism during the early stage of replicative cellular senescence in budding yeast.

Authors:  Yuka Kamei; Yoshihiro Tamada; Yasumune Nakayama; Eiichiro Fukusaki; Yukio Mukai
Journal:  J Biol Chem       Date:  2014-10-07       Impact factor: 5.157

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

4.  Quantitative evidence for early life fitness defects from 32 longevity-associated alleles in yeast.

Authors:  Joe R Delaney; Christopher J Murakami; Brady Olsen; Brian K Kennedy; Matt Kaeberlein
Journal:  Cell Cycle       Date:  2011-01-01       Impact factor: 4.534

Review 5.  Replicative and chronological aging in Saccharomyces cerevisiae.

Authors:  Valter D Longo; Gerald S Shadel; Matt Kaeberlein; Brian Kennedy
Journal:  Cell Metab       Date:  2012-07-03       Impact factor: 27.287

Review 6.  Yeast longevity and aging--the mitochondrial connection.

Authors:  S Michal Jazwinski
Journal:  Mech Ageing Dev       Date:  2005-02       Impact factor: 5.432

7.  The paths of mortality: how understanding the biology of aging can help explain systems behavior of single cells.

Authors:  Matthew M Crane; Matt Kaeberlein
Journal:  Curr Opin Syst Biol       Date:  2017-12-06

8.  Single cell analysis of yeast replicative aging using a new generation of microfluidic device.

Authors:  Yi Zhang; Chunxiong Luo; Ke Zou; Zhengwei Xie; Onn Brandman; Qi Ouyang; Hao Li
Journal:  PLoS One       Date:  2012-11-08       Impact factor: 3.240

9.  Nucleosome loss leads to global transcriptional up-regulation and genomic instability during yeast aging.

Authors:  Zheng Hu; Kaifu Chen; Zheng Xia; Myrriah Chavez; Sangita Pal; Ja-Hwan Seol; Chin-Chuan Chen; Wei Li; Jessica K Tyler
Journal:  Genes Dev       Date:  2014-02-15       Impact factor: 11.361

10.  Analysis of individual cells identifies cell-to-cell variability following induction of cellular senescence.

Authors:  Christopher D Wiley; James M Flynn; Christapher Morrissey; Ronald Lebofsky; Joe Shuga; Xiao Dong; Marc A Unger; Jan Vijg; Simon Melov; Judith Campisi
Journal:  Aging Cell       Date:  2017-07-11       Impact factor: 9.304

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  1 in total

1.  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

  1 in total

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