Literature DB >> 19421136

Quantifying yeast chronological life span by outgrowth of aged cells.

Christopher Murakami1, Matt Kaeberlein.   

Abstract

The budding yeast Saccharomyces cerevisiae has proven to be an important model organism in the field of aging research. The replicative and chronological life spans are two established paradigms used to study aging in yeast. Replicative aging is defined as the number of daughter cells a single yeast mother cell produces before senescence; chronological aging is defined by the length of time cells can survive in a non-dividing, quiescence-like state. We have developed a high-throughput method for quantitative measurement of chronological life span. This method involves aging the cells in a defined medium under agitation and at constant temperature. At each age-point, a sub-population of cells is removed from the aging culture and inoculated into rich growth medium. A high-resolution growth curve is then obtained for this sub-population of aged cells using a Bioscreen C MBR machine. An algorithm is then applied to determine the relative proportion of viable cells in each sub-population based on the growth kinetics at each age-point. This method requires substantially less time and resources compared to other chronological lifespan assays while maintaining reproducibility and precision. The high-throughput nature of this assay should allow for large-scale genetic and chemical screens to identify novel longevity modifiers for further testing in more complex organisms.

Entities:  

Mesh:

Year:  2009        PMID: 19421136      PMCID: PMC2762921          DOI: 10.3791/1156

Source DB:  PubMed          Journal:  J Vis Exp        ISSN: 1940-087X            Impact factor:   1.355


  5 in total

1.  Preadaptation to efficient respiratory maintenance is essential both for maximal longevity and the retention of replicative potential in chronologically ageing yeast.

Authors:  Peter W Piper; Nicholas L Harris; Morag MacLean
Journal:  Mech Ageing Dev       Date:  2006-06-19       Impact factor: 5.432

2.  A method for high-throughput quantitative analysis of yeast chronological life span.

Authors:  Christopher J Murakami; Christopher R Burtner; Brian K Kennedy; Matt Kaeberlein
Journal:  J Gerontol A Biol Sci Med Sci       Date:  2008-02       Impact factor: 6.053

Review 3.  Replicative aging in yeast: the means to the end.

Authors:  K A Steinkraus; M Kaeberlein; B K Kennedy
Journal:  Annu Rev Cell Dev Biol       Date:  2008       Impact factor: 13.827

4.  Superoxide is a mediator of an altruistic aging program in Saccharomyces cerevisiae.

Authors:  Paola Fabrizio; Luisa Battistella; Raffaello Vardavas; Cristina Gattazzo; Lee-Loung Liou; Alberto Diaspro; Janis W Dossen; Edith Butler Gralla; Valter D Longo
Journal:  J Cell Biol       Date:  2004-09-27       Impact factor: 10.539

Review 5.  The chronological life span of Saccharomyces cerevisiae.

Authors:  Paola Fabrizio; Valter D Longo
Journal:  Aging Cell       Date:  2003-04       Impact factor: 9.304

  5 in total
  41 in total

1.  A system to identify inhibitors of mTOR signaling using high-resolution growth analysis in Saccharomyces cerevisiae.

Authors:  Mitchell B Lee; Daniel T Carr; Michael G Kiflezghi; Yan Ting Zhao; Deborah B Kim; Socheata Thon; Margarete D Moore; Mary Ann K Li; Matt Kaeberlein
Journal:  Geroscience       Date:  2017-07-13       Impact factor: 7.713

2.  Translational Geroscience: From invertebrate models to companion animal and human interventions.

Authors:  Mitchell B Lee; Matt Kaeberlein
Journal:  Transl Med Aging       Date:  2018-08-17

3.  pH neutralization protects against reduction in replicative lifespan following chronological aging in yeast.

Authors:  Christopher Murakami; Joe R Delaney; Annie Chou; Daniel Carr; Jennifer Schleit; George L Sutphin; Elroy H An; Anthony S Castanza; Marissa Fletcher; Sarani Goswami; Sean Higgins; Mollie Holmberg; Jessica Hui; Monika Jelic; Ki-Soo Jeong; Jin R Kim; Shannon Klum; Eric Liao; Michael S Lin; Winston Lo; Hillary Miller; Richard Moller; Zhao J Peng; Tom Pollard; Prarthana Pradeep; Dillon Pruett; Dilreet Rai; Vanessa Ros; Alex Schuster; Minnie Singh; Benjamin L Spector; Helen Vander Wende; Adrienne M Wang; Brian M Wasko; Brady Olsen; Matt Kaeberlein
Journal:  Cell Cycle       Date:  2012-08-08       Impact factor: 4.534

4.  A genomic analysis of chronological longevity factors in budding yeast.

Authors:  Christopher R Burtner; Christopher J Murakami; Brady Olsen; Brian K Kennedy; Matt Kaeberlein
Journal:  Cell Cycle       Date:  2011-05-01       Impact factor: 4.534

Review 5.  Dietary restriction and lifespan: Lessons from invertebrate models.

Authors:  Pankaj Kapahi; Matt Kaeberlein; Malene Hansen
Journal:  Ageing Res Rev       Date:  2016-12-19       Impact factor: 10.895

Review 6.  Yeast as a model to understand the interaction between genotype and the response to calorie restriction.

Authors:  Jennifer Schleit; Brian M Wasko; Matt Kaeberlein
Journal:  FEBS Lett       Date:  2012-07-22       Impact factor: 4.124

7.  Dietary restriction and mitochondrial function link replicative and chronological aging in Saccharomyces cerevisiae.

Authors:  Joe R Delaney; Christopher Murakami; Annie Chou; Daniel Carr; Jennifer Schleit; George L Sutphin; Elroy H An; Anthony S Castanza; Marissa Fletcher; Sarani Goswami; Sean Higgins; Mollie Holmberg; Jessica Hui; Monika Jelic; Ki-Soo Jeong; Jin R Kim; Shannon Klum; Eric Liao; Michael S Lin; Winston Lo; Hillary Miller; Richard Moller; Zhao J Peng; Tom Pollard; Prarthana Pradeep; Dillon Pruett; Dilreet Rai; Vanessa Ros; Alex Schuster; Minnie Singh; Benjamin L Spector; Helen Vander Wende; Adrienne M Wang; Brian M Wasko; Brady Olsen; Matt Kaeberlein
Journal:  Exp Gerontol       Date:  2012-12-09       Impact factor: 4.032

8.  YODA: software to facilitate high-throughput analysis of chronological life span, growth rate, and survival in budding yeast.

Authors:  Brady Olsen; Christopher J Murakami; Matt Kaeberlein
Journal:  BMC Bioinformatics       Date:  2010-03-18       Impact factor: 3.169

9.  Gene-nutrient interaction markedly influences yeast chronological lifespan.

Authors:  Daniel L Smith; Crystal H Maharrey; Christopher R Carey; Richard A White; John L Hartman
Journal:  Exp Gerontol       Date:  2016-04-25       Impact factor: 4.032

10.  Sugar metabolism, redox balance and oxidative stress response in the respiratory yeast Kluyveromyces lactis.

Authors:  M Isabel González-Siso; Ana García-Leiro; Nuria Tarrío; M Esperanza Cerdán
Journal:  Microb Cell Fact       Date:  2009-08-30       Impact factor: 5.328

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.