A primer on pheromone signaling in Caenorhabditis elegans for systems biologists

Patrick T. McGrath*, Ilya Ruvinsky

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

23 Scopus citations

Abstract

Individuals communicate information about their age, sex, social status, and recent life history with other members of their species through the release of pheromones, chemical signals that elicit behavioral or physiological changes in the recipients. Pheromones provide a fascinating example of information exchange: animals have evolved intraspecific languages in the presence of eavesdroppers and cheaters. In this review, we discuss the recent work using the nematode C. elegans to decipher its chemical language through the analysis of ascaroside pheromones. Genetic dissection has started to identify the enzymes that produce pheromones and the neural circuits that process these signals. Ecological experiments have characterized the biotic environment of C. elegans and its relatives, including ecological relationships with a variety of species that sense or release similar blends of ascarosides. Systems biology approaches should be fruitful in understanding the organization and function of communication systems in C. elegans.

Original languageEnglish (US)
Pages (from-to)23-30
Number of pages8
JournalCurrent Opinion in Systems Biology
Volume13
DOIs
StatePublished - Feb 2019

Funding

We thank Rebecca Butcher and Frank Schroeder for comments on the manuscript and help with figures. This work was supported by NIH grant R01GM114170 to PTM and grants from NSF ( IOS-1708518 ) and NIH ( R01GM126125 ) to IR. We thank Rebecca Butcher and Frank Schroeder for comments on the manuscript and help with figures. This work was supported by NIH grant R01GM114170 to PTM and grants from NSF (IOS-1708518) and NIH (R01GM126125) to IR.

Keywords

  • Chemical communication
  • Chemoreceptors
  • Pheromones

ASJC Scopus subject areas

  • Modeling and Simulation
  • General Biochemistry, Genetics and Molecular Biology
  • Drug Discovery
  • Computer Science Applications
  • Applied Mathematics

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