Locomotion requires the interplay of the central nervous system (CNS), muscles, and the peripheral nervous system (PNS). Central pattern generators create the rhythms underlying locomotion, and sensory feedback from the PNS provides moment-by-moment adjustments to the pattern. However, we do not fully understand how the three systems interact to produce coordinated movement, or how genes encode development of the circuit.
To address this, we analyzed a simple behavioral circuit in a genetic model organism. Drosophila
larval crawling is based on a repetitive motor pattern. The muscles of each segment contract, then quickly relax and seamlessly propagate the wave to the next anterior segment, creating a peristaltic wave from tail to head. The larva can crawl at different speeds and change direction, but during motivated forward crawling the pattern is remarkably stereotyped and consists of a series of identical contraction waves (; Video 1
). This behavior results from a system comprising thirty muscles, thirty-one motorneurons, and forty-three sensory neurons in each abdominal hemisegment, plus an unknown number of interneurons (, D; Bate, 1993
; Landgraf et al., 1997
; Bodmer and Jan, 1987
). Larval crawling is an appealing system because the simplicity of the behavior and anatomy allow us to understand the circuit on the level of individual cells.
Larval crawling and its three interacting systems
larval crawling has been studied previously by a number of investigators. From this work we know about the role of specific genes in crawling behavior. For instance, mutations in K+
channel subunits produce dramatic effects on the crawling path, resulting in changes in speed, turning rate, and translocation efficiency (Wang et al, 1997
; Wang et al, 2002
; Ainsley et al, 2003
). We also know that the relative amounts of tyramine and octopamine play an important role in crawling persistance (Saraswati et al, 2003
; Fox et al, 2006
), and inhibiting dopaminergic cells results in circling behavior (Suster et al, 2003
). The relationships between motorneurons and their muscles has been well-mapped (Landgraf et al, 1997
), so we understand the motor output, but what generates the pattern of activity? Is there a well-defined central pattern generator? Does sensory feedback play an important role? Previous studies addressing the role of sensory feedback concluded that feedback is not necessary to produce the basic posterior to anterior contraction pattern, however, in each case the pattern was disrupted, suggesting that sensory feedback helps to shape the normal output (Suster and Bate 2002
; Fox et al, 2006
If sensory feedback is important for normal locomotion, which neurons play this role? Work on walking in adult Drosophila
and other insects has focused largely on the role of the chordotonal neurons and external sensory organs in organizing leg posture and movement (Kernan et al, 1994
; Bässler, 1988
; Burrows, 1996
; Zill et al, 2004
). However, at least one study suggests that multidendritic (or “multipolar”) sensory cells may play a role in adult walking (Guthrie, 1967
), and a study in Manduca
demonstrates an important role for certain multidendritic neurons in larval locomotion (Tamarkin and Levine, 1996
). In Drosophila
larvae, the multidendritic neurons form a complex web of specialized dendritic structures under the cuticle (Brewster and Bodmer, 1995
; Grueber et al, 2002
). Do these cells play a role in crawling behavior?
To answer these questions, we used techniques that allow us to analyze the Drosophila
crawling circuit at the level of small sets of individual neurons. The Gal4-UAS system allows manipulation of identifiable subsets of neurons with a variety of different Gal4 drivers (Brand and Perrimon, 1993
). Responder constructs such as UAS-shibirets
can be used to temporarily inhibit release of neurotransmitter in the neurons of an otherwise healthy animal (Kitamoto, 2001
; Thum et al., 2006
). Lastly, a GFP-tagged myosin heavy chain line (Mhc-GFP) allows us to directly image the activity of the muscles during crawling. This provides a more direct readout of the motor behavior than the traditional technique of analyzing the larval path, and the GFP-marked muscles reveal subtle defects in the motor pattern. A benefit of these approaches is that cells are studied in the intact animal rather than a reduced preparation, so we can study sensory as well as central neurons. In the work presented here, we focus on the role of body wall sensory neurons in crawling.
In our analysis, we found an important role for two classes of multidendritic neurons in larval crawling. These neurons appear to act as proprioceptors, sensing muscle contractions, and provide feedback to the CNS in a “mission-accomplished” signal that speeds the wave along. We found that disruption of dendritic morphology and axon pathfinding interferes with the feedback, suggesting that these neurons sense the contraction wave and pass that information on to central targets.