Literature DB >> 26170317

High-throughput analysis of yeast replicative aging using a microfluidic system.

Myeong Chan Jo1, Wei Liu2, Liang Gu3, Weiwei Dang4, Lidong Qin5.   

Abstract

Saccharomyces cerevisiae has been an important model for studying the molecular mechanisms of aging in eukaryotic cells. However, the laborious and low-throughput methods of current yeast replicative lifespan assays limit their usefulness as a broad genetic screening platform for research on aging. We address this limitation by developing an efficient, high-throughput microfluidic single-cell analysis chip in combination with high-resolution time-lapse microscopy. This innovative design enables, to our knowledge for the first time, the determination of the yeast replicative lifespan in a high-throughput manner. Morphological and phenotypical changes during aging can also be monitored automatically with a much higher throughput than previous microfluidic designs. We demonstrate highly efficient trapping and retention of mother cells, determination of the replicative lifespan, and tracking of yeast cells throughout their entire lifespan. Using the high-resolution and large-scale data generated from the high-throughput yeast aging analysis (HYAA) chips, we investigated particular longevity-related changes in cell morphology and characteristics, including critical cell size, terminal morphology, and protein subcellular localization. In addition, because of the significantly improved retention rate of yeast mother cell, the HYAA-Chip was capable of demonstrating replicative lifespan extension by calorie restriction.

Entities:  

Keywords:  Saccharomyces cerevisiae; calorie restriction; high-throughput; microfluidics; replicative aging

Mesh:

Substances:

Year:  2015        PMID: 26170317      PMCID: PMC4522780          DOI: 10.1073/pnas.1510328112

Source DB:  PubMed          Journal:  Proc Natl Acad Sci U S A        ISSN: 0027-8424            Impact factor:   11.205


  47 in total

1.  Logic of the yeast metabolic cycle: temporal compartmentalization of cellular processes.

Authors:  Benjamin P Tu; Andrzej Kudlicki; Maga Rowicka; Steven L McKnight
Journal:  Science       Date:  2005-10-27       Impact factor: 47.728

2.  Cell biology. Twists in the tale of the aging yeast.

Authors:  Jasper Rine
Journal:  Science       Date:  2005-11-18       Impact factor: 47.728

3.  The budding yeast protein Chl1p has a role in transcriptional silencing, rDNA recombination, and aging.

Authors:  Shankar Prasad Das; Pratima Sinha
Journal:  Biochem Biophys Res Commun       Date:  2005-11-11       Impact factor: 3.575

4.  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

5.  A memory system of negative polarity cues prevents replicative aging.

Authors:  Franz Meitinger; Anton Khmelinskii; Sandrine Morlot; Bahtiyar Kurtulmus; Saravanan Palani; Amparo Andres-Pons; Birgit Hub; Michael Knop; Gilles Charvin; Gislene Pereira
Journal:  Cell       Date:  2014-11-13       Impact factor: 41.582

6.  Genes determining yeast replicative life span in a long-lived genetic background.

Authors:  Matt Kaeberlein; Kathryn T Kirkland; Stanley Fields; Brian K Kennedy
Journal:  Mech Ageing Dev       Date:  2005-01-07       Impact factor: 5.432

7.  Microfluidics device for single cell gene expression analysis in Saccharomyces cerevisiae.

Authors:  James Ryley; Olivia M Pereira-Smith
Journal:  Yeast       Date:  2006 Oct-Nov       Impact factor: 3.239

8.  The DNA damage checkpoint response requires histone H2B ubiquitination by Rad6-Bre1 and H3 methylation by Dot1.

Authors:  Michele Giannattasio; Federico Lazzaro; Paolo Plevani; Marco Muzi-Falconi
Journal:  J Biol Chem       Date:  2005-01-04       Impact factor: 5.157

9.  Monitoring dynamics of single-cell gene expression over multiple cell cycles.

Authors:  Scott Cookson; Natalie Ostroff; Wyming Lee Pang; Dmitri Volfson; Jeff Hasty
Journal:  Mol Syst Biol       Date:  2005-11-22       Impact factor: 11.429

10.  Shortest-path network analysis is a useful approach toward identifying genetic determinants of longevity.

Authors:  J R Managbanag; Tarynn M Witten; Danail Bonchev; Lindsay A Fox; Mitsuhiro Tsuchiya; Brian K Kennedy; Matt Kaeberlein
Journal:  PLoS One       Date:  2008-11-25       Impact factor: 3.240

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  60 in total

1.  Maximum Caliber Can Build and Infer Models of Oscillation in a Three-Gene Feedback Network.

Authors:  Taylor Firman; Anar Amgalan; Kingshuk Ghosh
Journal:  J Phys Chem B       Date:  2019-01-09       Impact factor: 2.991

2.  A High-Throughput Screen for Yeast Replicative Lifespan Identifies Lifespan-Extending Compounds.

Authors:  Ethan A Sarnoski; Ping Liu; Murat Acar
Journal:  Cell Rep       Date:  2017-11-28       Impact factor: 9.423

Review 3.  Recent Developments in Single-Cell RNA-Seq of Microorganisms.

Authors:  Yi Zhang; Jiaxin Gao; Yanyi Huang; Jianbin Wang
Journal:  Biophys J       Date:  2018-06-26       Impact factor: 4.033

4.  Using Microfluidic Devices to Measure Lifespan and Cellular Phenotypes in Single Budding Yeast Cells.

Authors:  Ke Zou; Diana S Ren; Qi Ou-Yang; Hao Li; Jiashun Zheng
Journal:  J Vis Exp       Date:  2017-03-30       Impact factor: 1.355

Review 5.  The role of autophagy in the regulation of yeast life span.

Authors:  Jessica K Tyler; Jay E Johnson
Journal:  Ann N Y Acad Sci       Date:  2018-01-24       Impact factor: 5.691

6.  Aeroaging - A New Collaboration between Life Sciences Experts and Aerospace Engineers.

Authors:  M Vellas; C Fualdes; J E Morley; C Dray; L Rodriguez-Manas; A Meyer; L Michel; Y Rolland; Y Gourinat
Journal:  J Nutr Health Aging       Date:  2017       Impact factor: 4.075

7.  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 8.  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

9.  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

Review 10.  Recent Progress of Microfluidics in Translational Applications.

Authors:  Zongbin Liu; Xin Han; Lidong Qin
Journal:  Adv Healthc Mater       Date:  2016-03-22       Impact factor: 9.933

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