4.6 Article

Optimizing Dietary Restriction for Genetic Epistasis Analysis and Gene Discovery in C. elegans

期刊

PLOS ONE
卷 4, 期 2, 页码 -

出版社

PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pone.0004535

关键词

-

资金

  1. George E. Hewitt Foundation for Medical Research
  2. National Institutes of Health (NIH) [UCSD CMG Training Grant, R01 DK080425, P01 CA120964]
  3. NIH/NIA
  4. The Ellison Medical Foundation
  5. American Diabetes Association
  6. Howard Hughes Medical Institute

向作者/读者索取更多资源

Dietary restriction (DR) increases mammalian lifespan and decreases susceptibility to many age-related diseases. Lifespan extension due to DR is conserved across a wide range of species. Recent research has focused upon genetically tractable model organisms such as C. elegans to uncover the genetic mechanisms that regulate the response to DR, in the hope that this information will provide insight into the mammalian response and yield potential therapeutic targets. However, no consensus exists as to the best protocol to apply DR to C. elegans and potential key regulators of DR are protocol-specific. Here we define a DR method that better fulfills criteria required for an invertebrate DR protocol to mirror mammalian studies. The food intake that maximizes longevity varies for different genotypes and informative epistasis analysis with another intervention is only achievable at this 'optimal DR' level. Importantly therefore, the degree of restriction imposed using our method can easily be adjusted to determine the genotype-specific optimum DR level. We used this protocol to test two previously identified master regulators of DR in the worm. In contrast to previous reports, we find that DR can robustly extend the lifespan of worms lacking the AMP-activated protein kinase catalytic subunit AAK2 or the histone deacetylase SIR-2.1, highlighting the importance of first optimizing DR to identify universal regulators of DR mediated longevity.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.6
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据