Reactive chemicals and molecular processes occurring in living systems lead to the accumulation of informational and physical damage despite repair mechanisms. This wear-and-tear results in a growing likelihood of disease and death with time, referred to as aging. The random nature of damaging events contributes to the phenotypic divergence of individuals, even when they are genetically identical and share the same environment. This divergence results in a distribution of life spans that is reflective of the genotype. The complete survival curve of a population of isogenic individuals is therefore a powerful tool for classifying genes with regard to their impact on aging. The proposal aims at developing an automated, inexpensive, and robust system for obtaining high-resolution survival curves of the nematode C. elegans. The proposal will achieve this objective by adapting commercial flatbed scanners for long-term imaging of large worm populations and developing appropriate image processing software. Validation of the new method will occur by comparison with traditional manual procedures on four widely studied lifespan- extension mutants. The method's suitability for RNA interference studies will be assessed using similar comparisons. Such an automated system will have broad impact on the study of aging by revealing subtle genetic and environmental effects on survival that advance our understanding of major aging processes.
The survival curve of genetically identical individuals is a powerful tool in the study of aging. An automated, inexpensive, and robust system for obtaining high-resolution survival curves of large worm (C. elegans) populations will have broad impact on the study of aging by revealing subtle genetic and environmental effects on survival that advance our understanding of major aging pathways conserved across species. ? ? ?
| Fernandes de Abreu, Diana Andrea; Caballero, Antonio; Fardel, Pascal et al. (2014) An insulin-to-insulin regulatory network orchestrates phenotypic specificity in development and physiology. PLoS Genet 10:e1004225 |
| Stroustrup, Nicholas; Ulmschneider, Bryne E; Nash, Zachary M et al. (2013) The Caenorhabditis elegans Lifespan Machine. Nat Methods 10:665-70 |
