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

Abstract

We describe a scalable automated method for measuring the pharyngeal pumping of Caenorhabditis elegans in controlled environments. Our approach enables unbiased measurements for prolonged periods, a high throughput, and measurements in controlled yet dynamically changing feeding environments. The automated analysis compares well with scoring pumping by visual inspection, a common practice in the field. In addition, we we observed overall low rates of pharyngeal pumping and long correlation times when food availability was oscillated.

Introduction

The nematode Caenorhabditis elegans feeds by drawing bacteria suspended in liquid into its pharynx, a neuromuscular organ that functions as a pump. The cycle of contraction and relaxation that draws food from the environment and filters bacteria from liquid is referred to as pharyngeal pumping. About one out of four pharyngeal pumps is followed by a posterior moving peristaltic contraction that transports food past the pharyngeal isthmus. This is referred to as isthmus peristalsis and, while coupled to pumping, it is distinctly regulated (Avery 1987, Raizen 1994, Avery 2012, Song 2013). The rate of pumping is thus the primary indicator of food intake (Avery 1993).

The rate of pumping depends on feeding history, quality of food, and the familiarity of food (Shtonda 2006, Song 2013a, Hobson 2006). Counting the stereotypical motion observed in the terminal bulb of the pharynx enabled detailed analyses of neuronal and molecular mechanisms that regulate pumping. However, these regulatory pathways were predominantly examined in a stationary environment, containing a saturated, high abundance of (familiar) bacteria on a standard agar plate. Moreover, traditional feeding assays rely on manual scoring of the mean number of pumps over brief (typically 30 sec) intervals (Avery 1989, Raizen 1995, Song 2013a). The reduction of a potentially complex time-series to a single average rate may result in loss of pertinent information or even unintended bias.