Literature DB >> 27474347

A scalable method for automatically measuring pharyngeal pumping in C. elegans.

Monika Scholz1, Dylan J Lynch2, Kyung Suk Lee3, Erel Levine3, David Biron4.   

Abstract

BACKGROUND: The nematode Caenorhabditis elegans is widely used for studying small neural circuits underlying behavior. In particular, the rhythmic feeding motions collectively termed pharyngeal pumping are regulated by a nearly autonomous network of 20 neurons of 14 types. Despite much progress achieved through laser ablation, genetics, electrophysiology, and optogenetics, key questions regarding the regulation of pumping remain open. NEW
METHOD: We describe the implementation and application of a scalable automated method for measuring pumping in controlled environments. Our implementation is affordable and flexible: key hardware and software elements can be modified to accommodate different requirements.
RESULTS: We demonstrate prolonged measurements under controlled conditions and the resulting high quality data. We show the scalability of our method, enabling high throughput, and its suitability for maintaining static and dynamic conditions. When food availability was oscillated, pumping rates were low as compared to steady conditions and pumping activity was not reliably modulated in response to changes in food concentration. COMPARISON WITH EXISTING
METHOD: The prevailing method for measuring rates of pumping relies on scoring by visual inspection of short recordings. Our automated method compares well with manual scoring. It enables detailed statistical characterization under experimental conditions not previously accessible and minimizes unintentional bias.
CONCLUSIONS: Our approach adds a powerful tool for studying pharyngeal pumping. It enhances the experimental versatility of assaying genetic and pharmacological manipulations and the ability to characterize the resulting behavior. Both the experimental setup and the analysis can be readily adapted to additional challenging motion detection problems.
Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

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Mesh:

Year:  2016        PMID: 27474347     DOI: 10.1016/j.jneumeth.2016.07.016

Source DB:  PubMed          Journal:  J Neurosci Methods        ISSN: 0165-0270            Impact factor:   2.390


  12 in total

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