Abstract

Class I ventral posterior dendritic arborisation (c1vpda) proprioceptive sensory neurons respond to contractions in the Drosophila larval body wall during crawling. Their dendritic branches run along the direction of contraction, possibly a functional requirement to maximise membrane curvature during crawling contractions. Although the molecular machinery of dendritic patterning in c1vpda has been extensively studied, the process leading to the precise elaboration of their comb-like shapes remains elusive. Here, to link dendrite shape with its proprioceptive role, we performed long-term, non-invasive, in vivo time-lapse imaging of c1vpda embryonic and larval morphogenesis to reveal a sequence of differentiation stages. We combined computer models and dendritic branch dynamics tracking to propose that distinct sequential phases of stochastic growth and retraction achieve efficient dendritic trees both in terms of wire and function. Our study shows how dendrite growth balances structure-function requirements, shedding new light on general principles of self-organisation in functionally specialised dendrites.

Highlights

  • A fundamental open question in neuroscience is understanding how the shape of specific neuron classes arises during cell development to perform distinct computations (Carr et al, 2006)

  • To better understand the relationship between dendrite structure and function in c1vpda sensory neurons, we dissected the developmental process of apical dendrite formation quantitatively using long-term, non-invasive time-lapse imaging from embryonic stages (16 hrs after egg laying AEL) until early 3rd larval stage (72 hrs AEL) (Figure 1)

  • These findings indicate that a stochastic growth that satisfies wire constraints combined with random retraction of terminals are consistent with c1vpda dendrite morphogenesis and refinement

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Summary

Introduction

A fundamental open question in neuroscience is understanding how the shape of specific neuron classes arises during cell development to perform distinct computations (Carr et al, 2006). Technological and conceptual advances have allowed exciting discoveries on how the coupling of class type-specific dendrite geometry with various ion channels provide the substrate for signal processing and integration in dendrites (Mainen and Sejnowski, 1996; van Elburg and van Ooyen, 2010; Gabbiani et al, 2002; London and Hausser, 2005; Branco et al, 2010; Stuart and Spruston, 2015; Beaulieu-Laroche et al, 2018; Poirazi and Papoutsi, 2020).

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