Studies in short-lived model organisms, such as yeast, worms, flies, and mice have elucidated some of the genetic and environmental factors that influence aging. In order to make these findings relevant for human health will require a more complete picture of which of these factors are evolutionarily conserved and which are specific to individual organisms. This proposal attempts to move toward this goal by utilizing a recently developed quantitative high-throughput method for measuring yeast chronological life span. We propose to use this method in order to develop the most comprehensive understanding of aging in any organism to date. We will individually examine the potential role in aging for each component of the growth media and each gene in the genome. We will use the information derived from these studies, in combination with published genome-wide longevity screens in C. elegans, to determine which factors play a similar role in aging in both organisms. The evolutionary distance between yeast and worms is comparable to that between worms and humans, suggesting that if a particular gene has a conserved longevity-determining role in yeast and worms, there is a reasonable chance that role has been conserved in people. All of the data derived from these studies will be cataloged in an improved Aging Genes and Interventions Database. This database will also contain all of the information previously cataloged in the SAGE KE database and will be made freely available on our website.
We have recently developed a quantitative high-throughput method for measuring chronological life span in the budding yeast, Saccharomyces cerevisiae. The goal of this proposal is to use this method in order to define a majority of the genetic and environmental factors influencing aging in yeast. We will also determine which of these factors play a similar role in a multicellular organism, the nematode Caenorhabditis elegans. These studies will define evolutionarily conserved mechanisms of aging and factors that modulate aging, which will facilitate the development of interventions to treat age-associated diseases in people.
| Kaeberlein, Matt; Kennedy, Brian K (2012) A new chronological survival assay in mammalian cell culture. Cell Cycle 11:201-2 |
| Burtner, Christopher R; Murakami, Christopher J; Olsen, Brady et al. (2011) A genomic analysis of chronological longevity factors in budding yeast. Cell Cycle 10:1385-96 |
| Kaeberlein, Matt (2010) Lessons on longevity from budding yeast. Nature 464:513-9 |
| Olsen, Brady; Murakami, Christopher J; Kaeberlein, Matt (2010) YODA: software to facilitate high-throughput analysis of chronological life span, growth rate, and survival in budding yeast. BMC Bioinformatics 11:141 |
| Murakami, Christopher; Kaeberlein, Matt (2009) Quantifying yeast chronological life span by outgrowth of aged cells. J Vis Exp : |
| Burtner, Christopher R; Murakami, Christopher J; Kennedy, Brian K et al. (2009) A molecular mechanism of chronological aging in yeast. Cell Cycle 8:1256-70 |
