Deterministic and Stochastic Rules of Branching Govern Dendrite Morphogenesis of Sensory Neurons

Neurons exploit stochastic growth to rapidly and economically build dense radially oriented dendritic arbors

Dendrites grow by stochastic branching, elongation, and retraction. A key question is whether such a mechanism is sufficient to form highly branched dendritic morphologies. Alternatively, are signals from other cells or is the topological hierarchy of the growing network necessary for dendrite geometry? To answer these questions, we developed a mean-field model in which branch dynamics is isotropic and homogenous (i.e., no extrinsic instruction) and depends only on the average lengths and densities of branches. Branching is modeled as density-dependent nucleation so there are no tree structures and no network topology. Despite its simplicity, the model predicted several key morphological properties of class IV Drosophila sensory dendrites, including the exponential distribution of branch lengths, the parabolic scaling between dendrite number and length densities, the tight spacing of the dendritic meshwork (which required minimal total branch length), and the radial orientation of branches. Stochastic growth also accelerated the overall expansion rate of the arbor. Therefore, stochastic dynamics is an economical and rapid space-filling mechanism for building dendritic arbors without external guidance or hierarchical branching mechanisms. Our model provides a general theoretical framework for understanding how macroscopic branching patterns emerge from microscopic dynamics.

A dendritic guidance receptor functions in both ligand dependent and independent modes

The formation of an appropriately shaped dendritic arbor is critical for a neuron to receive information. Dendritic morphogenesis is a dynamic process involving growth, branching, and retraction. How the growth and stabilization of dendrites are coordinated at the molecular level remains a key question in developmental neurobiology. The highly arborized and stereotyped dendritic arbors of the Caenorhabditis elegans PVD neuron are shaped by the transmembrane DMA-1 receptor through its interaction with a tripartite ligand complex consisting of SAX-7, MNR-1, and LECT-2. However, receptor null mutants exhibit strongly reduced dendrite outgrowth, whereas ligand null mutants show disordered branch patterns, suggesting a ligand-independent function of the receptor. To test this idea, we identified point mutations in dma-1 that disrupt receptor-ligand binding and introduced corresponding mutations into the endogenous gene. We show that the ligand-free receptor is sufficient to drive robust, disordered dendritic branch formation but results in a complete loss of arbor shape. This disordered outgrowth program utilizes similar downstream effectors as the stereotyped outgrowth program, further arguing that ligand binding is not necessary for outgrowth. Finally, we demonstrate that ligand binding is required to maintain higher-order dendrites after development is complete. Taken together, our findings support a surprising model in which ligand-free and ligand-bound DMA-1 receptors have distinct functions: the ligand-free receptor promotes stochastic outgrowth and branching, whereas the ligand-bound receptor guides stereotyped dendrite morphology by stabilizing arbors at target locations.

Study of Dendrite Differentiation Using Drosophila Dendritic Arborization Neurons

Neurons receive, process, and integrate inputs. These operations are organized by dendrite arbor morphology, and the dendritic arborization (da) neurons of the Drosophila peripheral sensory nervous system are an excellent experimental model for examining the differentiation processes that build and shape the dendrite arbor. Studies in da neurons are enabled by a wealth of fly genetic tools that allow targeted neuron manipulation and labeling of the neuron's cytoskeletal or organellar components. Moreover, as da neuron dendrite arbors cover the body wall, they are highly accessible for live imaging analysis of arbor patterning. Here, we outline the structure and function of different da neuron types and give examples of how they are used to elucidate central mechanisms of dendritic arbor formation.

Mounting of Embryos, Larvae, and Pupae for Live Drosophila Dendritic Arborization Neuron Imaging

Live imaging approaches are essential for monitoring how neurons go through a coordinated series of differentiation steps in their native mechanical and chemical environment. These imaging approaches also allow the study of dynamic subcellular processes such as cytoskeleton remodeling and the movement of organelles. Drosophila dendritic arborization (da) neurons are a powerful experimental system for studying the dendrite arbor in live animals. da neurons are located on the internal surface of the body wall and, therefore, are easily accessible for imaging. Moreover, many genetic tools target da neurons to disrupt genes or proteins of interest and allow the investigator to visualize fluorescent markers and endogenously tagged proteins in the neurons. This protocol introduces methods for preparing and mounting intact Drosophila embryos, larvae, and pupae, allowing live imaging of dynamic cellular processes in da neurons.

The Drosophila tracheal terminal cell as a model for branching morphogenesis

The terminal cells of the Drosophila larval tracheal system are perhaps the simplest delivery networks, providing an analogue for mammalian vascular growth and function in a system with many fewer components. These cells are a prime example of single-cell morphogenesis, branching significantly over time to adapt to the needs of the growing tissue they supply. While the genetic mechanisms governing local branching decisions have been studied extensively, an understanding of the emergence of a global network architecture is still lacking. Mapping out the full network architecture of populations of terminal cells at different developmental times of Drosophila larvae, we find that cell growth follows scaling laws relating the total edge length, supply area, and branch density. Using time-lapse imaging of individual terminal cells, we identify that the cells grow in three ways: by extending branches, by the side budding of new branches, and by internally growing existing branches. A generative model based on these modes of growth recapitulates statistical properties of the terminal cell network data. These results suggest that the scaling laws arise from the coupled contributions of branching and internal growth. This study establishes the terminal cell as a uniquely tractable model system for further studies of transportation and distribution networks.

Gamma-protocadherins regulate dendrite self-recognition and dynamics to drive self-avoidance

Neurons form cell-type-specific morphologies that are shaped by cell-surface molecules and their cellular events governing dendrite growth. One growth rule is dendrite self-avoidance, whereby dendrites distribute uniformly within a neuron's territory by avoiding sibling branches. In mammalian neurons, dendrite self-avoidance is regulated by a large family of cell-recognition molecules called the clustered protocadherins (cPcdhs). Genetic and molecular studies suggest that the cPcdhs mediate homophilic recognition and repulsion between self-dendrites. However, this model has not been tested through direct investigation of self-avoidance during development. Here, we performed live imaging and four-dimensional (4D) quantifications of dendrite morphogenesis to define the dynamics and cPcdh-dependent mechanisms of self-avoidance. We focused on the mouse retinal starburst amacrine cell (SAC), which requires the gamma-Pcdhs (Pcdhgs) and self/non-self-recognition to establish a stereotypic radial morphology while permitting dendritic interactions with neighboring SACs. Through morphogenesis, SACs extend dendritic protrusions that iteratively fill the growing arbor and contact and retract from nearby self-dendrites. Compared to non-self-contacting protrusions, self-contacting events have longer lifetimes, and a subset persists as loops. In the absence of the Pcdhgs, non-self-contacting dynamics are unaffected but self-contacting retractions are significantly diminished. Self-contacting bridges accumulate, leading to the bundling of dendritic processes and disruption to the arbor shape. By tracking dendrite self-avoidance in real time, our findings establish that the γ-Pcdhs mediate self-recognition and retraction between contacting sibling dendrites. Our results also illustrate how self-avoidance shapes stochastic and space-filling dendritic outgrowth for robust pattern formation in mammalian neurons.

Augmin complex activity finetunes dendrite morphology through non-centrosomal microtubule nucleation in vivo

During development, neurons achieve a stereotyped neuron type-specific morphology, which relies on dynamic support by microtubules (MTs). An important player is the augmin complex (hereafter augmin), which binds to existing MT filaments and recruits the γ-tubulin ring complex (γ-TuRC), to form branched MTs. In cultured neurons, augmin is important for neurite formation. However, little is known about the role of augmin during neurite formation in vivo. Here, we have revisited the role of mammalian augmin in culture and then turned towards the class four Drosophila dendritic arborization (c4da) neurons. We show that MT density is maintained through augmin in cooperation with the γ-TuRC in vivo. Mutant c4da neurons show a reduction of newly emerging higher-order dendritic branches and in turn also a reduced number of their characteristic space-filling higher-order branchlets. Taken together, our data reveal a cooperative function for augmin with the γ-TuRC in forming enough MTs needed for the appropriate differentiation of morphologically complex dendrites in vivo.

Long-term day-by-day tracking of microvascular networks sprouting in fibrin gels: From detailed morphological analyses to general growth rules

Understanding and controlling of the evolution of sprouting vascular networks remains one of the basic challenges in tissue engineering. Previous studies on the vascularization dynamics have typically focused only on the phase of intense growth and often lacked spatial control over the initial cell arrangement. Here, we perform long-term day-by-day analysis of tens of isolated microvasculatures sprouting from endothelial cell-coated spherical beads embedded in an external fibrin gel. We systematically study the topological evolution of the sprouting networks over their whole lifespan, i.e., for at least 14 days. We develop a custom image analysis toolkit and quantify (i) the overall length and area of the sprouts, (ii) the distributions of segment lengths and branching angles, and (iii) the average number of branch generations-a measure of network complexity. We show that higher concentrations of vascular endothelial growth factor (VEGF) lead to earlier sprouting and more branched networks, yet without significantly affecting the speed of growth of individual sprouts. We find that the mean branching angle is weakly dependent on VEGF and typically in the range of 60°-75°, suggesting that, by comparison with the available diffusion-limited growth models, the bifurcating tips tend to follow local VEGF gradients. At high VEGF concentrations, we observe exponential distributions of segment lengths, which signify purely stochastic branching. Our results-due to their high statistical relevance-may serve as a benchmark for predictive models, while our new image analysis toolkit, offering unique features and high speed of operation, could be exploited in future angiogenic drug tests.

A biologically inspired repair mechanism for neuronal reconstructions with a focus on human dendrites

Investigating and modelling the functionality of human neurons remains challenging due to the technical limitations, resulting in scarce and incomplete 3D anatomical reconstructions. Here we used a morphological modelling approach based on optimal wiring to repair the parts of a dendritic morphology that were lost due to incomplete tissue samples. In Drosophila, where dendritic regrowth has been studied experimentally using laser ablation, we found that modelling the regrowth reproduced a bimodal distribution between regeneration of cut branches and invasion by neighbouring branches. Interestingly, our repair model followed growth rules similar to those for the generation of a new dendritic tree. To generalise the repair algorithm from Drosophila to mammalian neurons, we artificially sectioned reconstructed dendrites from mouse and human hippocampal pyramidal cell morphologies, and showed that the regrown dendrites were morphologically similar to the original ones. Furthermore, we were able to restore their electrophysiological functionality, as evidenced by the recovery of their firing behaviour. Importantly, we show that such repairs also apply to other neuron types including hippocampal granule cells and cerebellar Purkinje cells. We then extrapolated the repair to incomplete human CA1 pyramidal neurons, where the anatomical boundaries of the particular brain areas innervated by the neurons in question were known. Interestingly, the repair of incomplete human dendrites helped to simulate the recently observed increased synaptic thresholds for dendritic NMDA spikes in human versus mouse dendrites. To make the repair tool available to the neuroscience community, we have developed an intuitive and simple graphical user interface (GUI), which is available in the TREES toolbox (www.treestoolbox.org).

Memory consolidation in honey bees is enhanced by down-regulation of Down syndrome cell adhesion molecule and changes its alternative splicing

Down syndrome cell adhesion molecule (Dscam) gene encodes a cell adhesion molecule required for neuronal wiring. A remarkable feature of arthropod Dscam is massive alternative splicing generating thousands of different isoforms from three variable clusters of alternative exons. Dscam expression and diversity arising from alternative splicing have been studied during development, but whether they exert functions in adult brains has not been determined. Here, using honey bees, we find that Dscam expression is critically linked to memory retention as reducing expression by RNAi enhances memory after reward learning in adult worker honey bees. Moreover, alternative splicing of Dscam is altered in all three variable clusters after learning. Since identical Dscam isoforms engage in homophilic interactions, these results suggest a mechanism to alter inclusion of variable exons during memory consolidation to modify neuronal connections for memory retention.

Sculpting the dendritic landscape: Actin, microtubules, and the art of arborization

Dendrites are intricately designed neuronal compartments that play a vital role in the gathering and processing of sensory or synaptic inputs. Their diverse and elaborate structures are distinct features of neuronal organization and function. Central to the generation of these dendritic arbors is the neuronal cytoskeleton. In this review, we delve into the current progress toward our understanding of how dendrite arbors are generated and maintained, focusing on the role of the actin and microtubule cytoskeleton.

Self-organized and directed branching results in optimal coverage in developing dermal lymphatic networks

Branching morphogenesis is a ubiquitous process that gives rise to high exchange surfaces in the vasculature and epithelial organs. Lymphatic capillaries form branched networks, which play a key role in the circulation of tissue fluid and immune cells. Although mouse models and correlative patient data indicate that the lymphatic capillary density directly correlates with functional output, i.e., tissue fluid drainage and trafficking efficiency of dendritic cells, the mechanisms ensuring efficient tissue coverage remain poorly understood. Here, we use the mouse ear pinna lymphatic vessel network as a model system and combine lineage-tracing, genetic perturbations, whole-organ reconstructions and theoretical modeling to show that the dermal lymphatic capillaries tile space in an optimal, space-filling manner. This coverage is achieved by two complementary mechanisms: initial tissue invasion provides a non-optimal global scaffold via self-organized branching morphogenesis, while VEGF-C dependent side-branching from existing capillaries rapidly optimizes local coverage by directionally targeting low-density regions. With these two ingredients, we show that a minimal biophysical model can reproduce quantitatively whole-network reconstructions, across development and perturbations. Our results show that lymphatic capillary networks can exploit local self-organizing mechanisms to achieve tissue-scale optimization.

Efficient simulation of neural development using shared memory parallelization

The Neural Development Simulator, NeuroDevSim, is a Python module that simulates the most important aspects of brain development: morphological growth, migration, and pruning. It uses an agent-based modeling approach inherited from the NeuroMaC software. Each cycle has agents called fronts execute model-specific code. In the case of a growing dendritic or axonal front, this will be a choice between extension, branching, or growth termination. Somatic fronts can migrate to new positions and any front can be retracted to prune parts of neurons. Collision detection prevents new or migrating fronts from overlapping with existing ones. NeuroDevSim is a multi-core program that uses an innovative shared memory approach to achieve parallel processing without messaging. We demonstrate linear strong parallel scaling up to 96 cores for large models and have run these successfully on 128 cores. Most of the shared memory parallelism is achieved without memory locking. Instead, cores have only write privileges to private sections of arrays, while being able to read the entire shared array. Memory conflicts are avoided by a coding rule that allows only active fronts to use methods that need writing access. The exception is collision detection, which is needed to avoid the growth of physically overlapping structures. For collision detection, a memory-locking mechanism was necessary to control access to grid points that register the location of nearby fronts. A custom approach using a serialized lock broker was able to manage both read and write locking. NeuroDevSim allows easy modeling of most aspects of neural development for models simulating a few complex or thousands of simple neurons or a mixture of both.

Code available at

https://github.com/CNS-OIST/NeuroDevSim.

A systematic CRISPR screen reveals redundant and specific roles for Dscam1 isoform diversity in neuronal wiring

Drosophila melanogaster Down syndrome cell adhesion molecule 1 (Dscam1) encodes 19,008 diverse ectodomain isoforms via the alternative splicing of exon 4, 6, and 9 clusters. However, whether individual isoforms or exon clusters have specific significance is unclear. Here, using phenotype-diversity correlation analysis, we reveal the redundant and specific roles of Dscam1 diversity in neuronal wiring. A series of deletion mutations were performed from the endogenous locus harboring exon 4, 6, or 9 clusters, reducing to 396 to 18,612 potential ectodomain isoforms. Of the 3 types of neurons assessed, dendrite self/non-self discrimination required a minimum number of isoforms (approximately 2,000), independent of exon clusters or isoforms. In contrast, normal axon patterning in the mushroom body and mechanosensory neurons requires many more isoforms that tend to associate with specific exon clusters or isoforms. We conclude that the role of the Dscam1 diversity in dendrite self/non-self discrimination is nonspecifically mediated by its isoform diversity. In contrast, a separate role requires variable domain- or isoform-related functions and is essential for other neurodevelopmental contexts, such as axonal growth and branching. Our findings shed new light on a general principle for the role of Dscam1 diversity in neuronal wiring.

Brain-wide dendrites in a near-optimal performance of dynamic range and information transmission

Dendrites receive and process signals from other neurons. The range of signal intensities that can be robustly distinguished by dendrites is quantified by the dynamic range. We investigate the dynamic range and information transmission efficiency of dendrites in relation to dendritic morphology. We model dendrites in a neuron as multiple excitable binary trees connected to the soma where each node in a tree can be excited by external stimulus or by receiving signals transmitted from adjacent excited nodes. It has been known that larger dendritic trees have a higher dynamic range. We show that for dendritic tress of the same number of nodes, the dynamic range increases with the number of somatic branches and decreases with the asymmetry of dendrites, and the information transmission is more efficient for dendrites with more somatic branches. Moreover, our simulated data suggest that there is an exponential association (decay resp.) of overall relative energy consumption (dynamic range resp.) in relation to the number of somatic branches. This indicates that further increasing the number of somatic branches (e.g. beyond 10 somatic branches) has limited ability to improve the transmission efficiency. With brain-wide neuron digital reconstructions of the pyramidal cells, 90% of neurons have no more than 10 dendrites. These suggest that actual brain-wide dendritic morphology is near optimal in terms of both dynamic range and information transmission.

Cis mutagenesis in vivo reveals extensive noncanonical functions of Dscam1 isoforms in neuronal wiring

Drosophila Down syndrome cell adhesion molecule 1 (Dscam1) encodes tens of thousands of cell recognition molecules via alternative splicing, which are required for neural function. A canonical self-avoidance model seems to provide a central mechanistic basis for Dscam1 functions in neuronal wiring. Here, we reveal extensive noncanonical functions of Dscam1 isoforms in neuronal wiring. We generated a series of allelic cis mutations in Dscam1, encoding a normal number of isoforms, but with an altered isoform composition. Despite normal dendritic self-avoidance and self-/nonself-discrimination in dendritic arborization (da) neurons, which is consistent with the canonical self-avoidance model, these mutants exhibited strikingly distinct spectra of phenotypic defects in the three types of neurons: up to ∼60% defects in mushroom bodies, a significant increase in branching and growth in da neurons, and mild axonal branching defects in mechanosensory neurons. Remarkably, the altered isoform composition resulted in increased dendrite growth yet inhibited axon growth. Moreover, reducing Dscam1 dosage exacerbated axonal defects in mushroom bodies and mechanosensory neurons but reverted dendritic branching and growth defects in da neurons. This splicing-tuned regulation strategy suggests that axon and dendrite growth in diverse neurons cell-autonomously require Dscam1 isoform composition. These findings provide important insights into the functions of Dscam1 isoforms in neuronal wiring.

Spatiotemporal changes in microtubule dynamics during dendritic morphogenesis

Dendritic morphogenesis requires dynamic microtubules (MTs) to form a coordinated cytoskeletal network during development. Dynamic MTs are characterized by their number, polarity and speed of polymerization. Previous studies described a correlation between anterograde MT growth and terminal branch extension in Drosophila dendritic arborization (da) neurons, suggesting a model that anterograde MT polymerization provides a driving force for dendritic branching. We recently found that the Ste20-like kinase Tao specifically regulates dendritic branching by controlling the number of dynamic MTs in a kinase activity-dependent fashion, without affecting MT polarity or speed. This finding raises the interesting question of how MT dynamics affects dendritic morphogenesis, and if Tao kinase activity is developmentally regulated to coordinate MT dynamics and dendritic morphogenesis. We explored the possible correlation between MT dynamics and dendritic morphogenesis together with the activity changes of Tao kinase in C1da and C4da neurons during larval development. Our data show that spatiotemporal changes in the number of dynamic MTs, but not polarity or polymerization speed, correlate with dendritic branching and Tao kinase activity. Our findings suggest that Tao kinase limits dendritic branching by controlling the abundance of dynamic MTs and we propose a novel model on how regulation of MT dynamics might influence dendritic morphogenesis.

How to build an epithelial tree

Nature has evolved a variety of mechanisms to build epithelial trees of diverse architectures within different organs and across species. Epithelial trees are elaborated through branch initiation and extension, and their morphogenesis ends with branch termination. Each of these steps of the branching process can be driven by the actions of epithelial cells themselves (epithelial-intrinsic mechanisms) or by the cells of their surrounding tissues (epithelial-extrinsic mechanisms). Here, we describe examples of how these mechanisms drive each stage of branching morphogenesis, drawing primarily from studies of the lung, kidney, salivary gland, mammary gland, and pancreas, all of which contain epithelial trees that form through collective cell behaviors. Much of our understanding of epithelial branching comes from experiments using mice, but we also include examples here from avian and reptilian models. Throughout, we highlight how distinct mechanisms are employed in different organs and species to build epithelial trees. We also highlight how similar morphogenetic motifs are used to carry out conserved developmental programs or repurposed to support novel ones. Understanding the unique strategies used by nature to build branched epithelia from across the tree of life can help to inspire creative solutions to problems in tissue engineering and regenerative medicine.

Dynamic instability of dendrite tips generates the highly branched morphologies of sensory neurons

The highly ramified arbors of neuronal dendrites provide the substrate for the high connectivity and computational power of the brain. Altered dendritic morphology is associated with neuronal diseases. Many molecules have been shown to play crucial roles in shaping and maintaining dendrite morphology. However, the underlying principles by which molecular interactions generate branched morphologies are not understood. To elucidate these principles, we visualized the growth of dendrites throughout larval development of Drosophila sensory neurons and found that the tips of dendrites undergo dynamic instability, transitioning rapidly and stochastically between growing, shrinking, and paused states. By incorporating these measured dynamics into an agent-based computational model, we showed that the complex and highly variable dendritic morphologies of these cells are a consequence of the stochastic dynamics of their dendrite tips. These principles may generalize to branching of other neuronal cell types, as well as to branching at the subcellular and tissue levels.

Self-avoidance alone does not explain the function of Dscam1 in mushroom body axonal wiring

Alternative splicing of Drosophila Dscam1 into 38,016 isoforms provides neurons with a unique molecular code for self-recognition and self-avoidance. A canonical model suggests that the homophilic binding of identical Dscam1 isoforms on the sister branches of mushroom body (MB) axons supports segregation with high fidelity, even when only a single isoform is expressed. Here, we generated a series of mutant flies with a single exon 4, 6, or 9 variant, encoding 1,584, 396, or 576 potential isoforms, respectively. Surprisingly, most of the mutants in the latter two groups exhibited obvious defects in the growth, branching, and segregation of MB axonal sister branches. This demonstrates that the repertoires of 396 and 576 Dscam1 isoforms were not sufficient for the normal patterning of axonal branches. Moreover, reducing Dscam1 levels largely reversed the defects caused by reduced isoform diversity, suggesting a functional link between Dscam1 expression levels and isoform diversity. Taken together, these results indicate that canonical self-avoidance alone does not explain the function of Dscam1 in MB axonal wiring.

The branching code: A model of actin-driven dendrite arborization

The cytoskeleton is crucial for defining neuronal-type-specific dendrite morphologies. To explore how the complex interplay of actin-modulatory proteins (AMPs) can define neuronal types in vivo, we focused on the class III dendritic arborization (c3da) neuron of Drosophila larvae. Using computational modeling, we reveal that the main branches (MBs) of c3da neurons follow general models based on optimal wiring principles, while the actin-enriched short terminal branches (STBs) require an additional growth program. To clarify the cellular mechanisms that define this second step, we thus concentrated on STBs for an in-depth quantitative description of dendrite morphology and dynamics. Applying these methods systematically to mutants of six known and novel AMPs, we revealed the complementary roles of these individual AMPs in defining STB properties. Our data suggest that diverse dendrite arbors result from a combination of optimal-wiring-related growth and individualized growth programs that are neuron-type specific.

Forced into shape: Mechanical forces in Drosophila development and homeostasis

Mechanical forces play a central role in shaping tissues during development and maintaining epithelial integrity in homeostasis. In this review, we discuss the roles of mechanical forces in Drosophila development and homeostasis, starting from the interplay of mechanics with cell growth and division. We then discuss several examples of morphogenetic processes where complex 3D structures are shaped by mechanical forces, followed by a closer look at patterning processes. We also review the role of forces in homeostatic processes, including cell elimination and wound healing. Finally, we look at the interplay of mechanics and developmental robustness and discuss open questions in the field, as well as novel approaches that will help tackle them in the future.

Theory of branching morphogenesis by local interactions and global guidance

Branching morphogenesis governs the formation of many organs such as lung, kidney, and the neurovascular system. Many studies have explored system-specific molecular and cellular regulatory mechanisms, as well as self-organizing rules underlying branching morphogenesis. However, in addition to local cues, branched tissue growth can also be influenced by global guidance. Here, we develop a theoretical framework for a stochastic self-organized branching process in the presence of external cues. Combining analytical theory with numerical simulations, we predict differential signatures of global vs. local regulatory mechanisms on the branching pattern, such as angle distributions, domain size, and space-filling efficiency. We find that branch alignment follows a generic scaling law determined by the strength of global guidance, while local interactions influence the tissue density but not its overall territory. Finally, using zebrafish innervation as a model system, we test these key features of the model experimentally. Our work thus provides quantitative predictions to disentangle the role of different types of cues in shaping branched structures across scales.

Quantifying neuronal structural changes over time using dynamic morphometrics

Brain circuit development involves tremendous structural formation and rearrangement of dendrites, axons, and the synaptic connections between them. Direct studies of neuronal morphogenesis are now possible through recent developments in multiple technologies, including single-neuron labeling, time-lapse imaging in intact tissues, and 4D rendering software capable of tracking neural growth over periods spanning minutes to days. These methods allow detailed quantification of structural changes of neurons over time, called dynamic morphometrics, providing new insights into fundamental growth patterns, underlying molecular mechanisms, and the intertwined influences of external factors, including neural activity, and intrinsic genetic programs. Here, we review the methods of dynamic morphometrics sampling and analyses, focusing on their applications to studies of activity-driven dendritogenesis in vertebrate systems.

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

Neuronal dendrites receive, integrate, and process numerous inputs and therefore serve as the neuron's "antennae". Dendrites display extreme morphological diversity across different neuronal classes to match the neuron's specific functional requirements. Understanding how this structural diversity is specified is therefore important for shedding light on information processing in the healthy and diseased nervous system. Popular models for in vivo studies of dendrite differentiation are the four classes of dendritic arborization (c1da-c4da) neurons of Drosophila larvae with their class-specific dendritic morphologies. Using da neurons, a combination of live-cell imaging and computational approaches have delivered information on the distinct phases and the time course of dendrite development from embryonic stages to the fully developed dendritic tree. With these data, we can start approaching the basic logic behind differential dendrite development. A major role in the definition of neuron-type specific morphologies is played by dynamic actin-rich processes and the regulation of their properties. This review presents the differences in the growth programs leading to morphologically different dendritic trees, with a focus on the key role of actin modulatory proteins. In addition, we summarize requirements and technological progress towards the visualization and manipulation of such actin regulators in vivo.

Dendrite enlightenment

Neuronal dendrites acquire complex morphologies during development. These are not just the product of cell-intrinsic developmental programs; rather they are defined in close interaction with the cellular environment. Thus, to understand the molecular cascades that yield appropriate morphologies, it is essential to investigate them in vivo, in the actual complex tissue environment encountered by the differentiating neuron in the developing animal. Particularly, genetic approaches have pointed to factors controlling dendrite differentiation in vivo. These suggest that localized and transient molecular cascades might underlie the formation and stabilization of dendrite branches with neuron type-specific characteristics. Here, I highlight the need for studies of neuronal dendrite differentiation in the animal, the challenges provided by such an approach, and the promising pathways that have recently opened.

Programmed and self-organized flow of information during morphogenesis

How the shape of embryos and organs emerges during development is a fundamental question that has fascinated scientists for centuries. Tissue dynamics arise from a small set of cell behaviours, including shape changes, cell contact remodelling, cell migration, cell division and cell extrusion. These behaviours require control over cell mechanics, namely active stresses associated with protrusive, contractile and adhesive forces, and hydrostatic pressure, as well as material properties of cells that dictate how cells respond to active stresses. In this Review, we address how cell mechanics and the associated cell behaviours are robustly organized in space and time during tissue morphogenesis. We first outline how not only gene expression and the resulting biochemical cues, but also mechanics and geometry act as sources of morphogenetic information to ultimately define the time and length scales of the cell behaviours driving morphogenesis. Next, we present two idealized modes of how this information flows - how it is read out and translated into a biological effect - during morphogenesis. The first, akin to a programme, follows deterministic rules and is hierarchical. The second follows the principles of self-organization, which rests on statistical rules characterizing the system's composition and configuration, local interactions and feedback. We discuss the contribution of these two modes to the mechanisms of four very general classes of tissue deformation, namely tissue folding and invagination, tissue flow and extension, tissue hollowing and, finally, tissue branching. Overall, we suggest a conceptual framework for understanding morphogenetic information that encapsulates genetics and biochemistry as well as mechanics and geometry as information modules, and the interplay of deterministic and self-organized mechanisms of their deployment, thereby diverging considerably from the traditional notion that shape is fully encoded and determined by genes.

Achieving functional neuronal dendrite structure through sequential stochastic growth and retraction

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.