The branching code: a model of actin-driven dendrite arborisation

Abstract

SummaryDendrites display a striking variety of neuronal type-specific morphologies, but the mechanisms and principles underlying such diversity remain elusive. A major player in defining the morphology of dendrites is the neuronal cytoskeleton, including evolutionarily conserved actin-modulatory proteins (AMPs). Still, we lack a clear understanding of how AMPs might support developmental phenomena such as neuron-type specific dendrite dynamics. To address precisely this level of in vivo specificity, we concentrated on a defined neuronal type, the class III dendritic arborisation (c3da) neuron of Drosophila larvae, displaying actin-enriched short terminal branchlets (STBs). Computational modelling reveals that the main branches of c3da neurons follow a general growth model based on optimal wiring, but the STBs do not. Instead, model STBs are defined by a short reach and a high affinity to grow towards the main branches. We thus concentrated on c3da STBs and developed new methods to quantitatively describe dendrite morphology and dynamics based on in vivo time-lapse imaging of mutants lacking individual AMPs. In this way, we extrapolated the role of these AMPs in defining STB properties. We propose that dendrite diversity is supported by the combination of a common step, refined by a neuron type-specific second level. For c3da neurons, we present a molecular model of how the combined action of multiple AMPs in vivo define the properties of these second level specialisations, the STBs.In briefA quantitative morphological dissection of the concerted actin-modulatory protein actions provides a model of dendrite branchlet outgrowth.HighlightsActin organisation in small terminal branchlets of Drosophila class III dendritic arborisation neuronsSix actin-modulatory proteins individually control the characteristic morphology and dynamics of branchletsQuantitative tools for dendrite morphology and branch dynamics enable a comparative analysisA two-step computational growth model reproduces c3da dendrite morphology

Drosophila Dendritic Arborisation Neurons: Fantastic Actin Dynamics and Where to Find Them

“…However, the properties of their characteristic short terminal branchlets cannot be reproduced by such models. Instead, a second step is required to distribute short dendritic branches along the main branches with increasing probability towards the terminals [13].…”

“…This fusion protein does not interfere with the developing cytoskeleton and distinctly labels F-actin during nucleation, without unspecific background fluorescence [60,61]. Analysis of branches newly forming, extending, retracting, and disappearing can be monitored within a range of 30 min [13]. (E) Dynamics of actin patches (LifeAct, here shown in red) along dendritic branches of c4da neurons, accumulating before new branch formation and extending into the newly formed branchlet [26].…”

“…(G) Bleaching and subsequent recovery of the GFP-actin signal at the tip of a growing dendritic branchlet of a c3da neuron. The most commonly used bulk kinetics approach method to study actin structure was performed in vivo to define the orientation of actin filaments in the extending branchlet [13].…”

“…The mechanisms governing the outgrowth of the primary dendrites, their branching, and the stabilization of newly developed branches, all need to work coherently to achieve a fully functional dendritic tree. In recent years, with the continued support of modeling approaches, growth programs underlying the patterns of dendritic arborization and organization have been identified [11][12][13][14]. These models suggest deterministic and stochastic steps in a segmented/iterative growth program.…”

“…These models suggest deterministic and stochastic steps in a segmented/iterative growth program. Very recent studies even propose similar generalized growth programs for different neuron types [11][12][13]15]. Implementation of these programs is mediated by transcription factors [16][17][18][19] and other modulating stimuli such as external interaction cues [20][21][22].…”