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J Vis Exp. 2018 Jun 29;(136). doi: 10.3791/57819.

The Replica Set Method: A High-throughput Approach to Quantitatively Measure Caenorhabditis elegans Lifespan.

Author information

1
Department of Biomedical Genetics, University of Rochester Medical Center.
2
Department of Biostatistics and Computational Biology, University of Rochester Medical Center; Non-Clinical Statistics, Bristol-Myers Squibb.
3
Department of Microbiology and Immunology, University of Rochester Medical Center.
4
Department of Biomedical Genetics, University of Rochester Medical Center; andrew_samuelson@urmc.rochester.edu.

Abstract

The Replica Set method is an approach to quantitatively measure lifespan or survival of Caenorhabditis elegans nematodes in a high-throughput manner, thus allowing a single investigator to screen more treatments or conditions over the same amount of time without loss of data quality. The method requires common equipment found in most laboratories working with C. elegans and is thus simple to adopt. The approach centers on assaying independent samples of a population at each observation point, rather than a single sample over time as with traditional longitudinal methods. Scoring entails adding liquid to the wells of a multi-well plate, which stimulates C. elegans to move and facilitates quantifying changes in healthspan. Other major benefits of the Replica Set method include reduced exposure of agar surfaces to airborne contaminants (e.g. mold or fungus), minimal handling of animals, and robustness to sporadic mis-scoring (such as calling an animal as dead when it is still alive). To appropriately analyze and visualize the data from a Replica Set style experiment, a custom software tool was also developed. Current capabilities of the software include plotting of survival curves for both Replica Set and traditional (Kaplan-Meier) experiments, as well as statistical analysis for Replica Set. The protocols provided here describe the traditional experimental approach and the Replica Set method, as well as an overview of the corresponding data analysis.

PMID:
30010651
PMCID:
PMC6102014
[Available on 2020-06-29]
DOI:
10.3791/57819
[Indexed for MEDLINE]

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