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Sci Rep. 2016 Oct 11;6:34859. doi: 10.1038/srep34859.

A network approach to discerning the identities of C. elegans in a free moving population.

Author information

1
Department of Chemical and Biological Engineering, Northwestern University, Evanston, IL, USA.
2
Department of Molecular Biosciences, Rice Institute for Biomedical Sciences, Northwestern University, Evanston, IL, USA.
3
Life and Health Sciences Research Institute (ICVS), School of Health Sciences, University of Minho, Braga, Portugal; ICVS/3B's - PT Government Associate Laboratory, Braga/Guimarães, Portugal.
4
Department of Physics and Astronomy, Northwestern University, Evanston, IL, USA.
5
Northwestern Institute on Complex Systems and Data Science, Northwestern University, Evanston, IL, USA.
6
Howard Hughes Medical Institute, Northwestern University, Evanston, IL, USA.

Abstract

The study of C. elegans has led to ground-breaking discoveries in gene-function, neuronal circuits, and physiological responses. Subtle behavioral phenotypes, however, are often difficult to measure reproducibly. We have developed an experimental and computational infrastructure to simultaneously record and analyze the physical characteristics, movement, and social behaviors of dozens of interacting free-moving nematodes. Our algorithm implements a directed acyclic network that reconstructs the complex behavioral trajectories generated by individual C. elegans in a free moving population by chaining hundreds to thousands of short tracks into long contiguous trails. This technique allows for the high-throughput quantification of behavioral characteristics that require long-term observation of individual animals. The graphical interface we developed will enable researchers to uncover, in a reproducible manner, subtle time-dependent behavioral phenotypes that will allow dissection of the molecular mechanisms that give rise to organism-level behavior.

PMID:
27725712
PMCID:
PMC5057085
DOI:
10.1038/srep34859
[Indexed for MEDLINE]
Free PMC Article

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