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BigNeuron is an open community bench-testing platform with the goal of setting open standards for accurate and fast automatic neuron tracing. We gathered a diverse set of image volumes across several species that is representative of the data obtained in many neuroscience laboratories interested in neuron tracing. Here, we report generated gold standard manual annotations for a subset of the available imaging datasets and quantified tracing quality for 35 automatic tracing algorithms. The goal of generating such a hand-curated diverse dataset is to advance the development of tracing algorithms and enable generalizable benchmarking. Together with image quality features, we pooled the data in an interactive web application that enables users and developers to perform principal component analysis, t-distributed stochastic neighbor embedding, correlation and clustering, visualization of imaging and tracing data, and benchmarking of automatic tracing algorithms in user-defined data subsets. The image quality metrics explain most of the variance in the data, followed by neuromorphological features related to neuron size. We observed that diverse algorithms can provide complementary information to obtain accurate results and developed a method to iteratively combine methods and generate consensus reconstructions. The consensus trees obtained provide estimates of the neuron structure ground truth that typically outperform single algorithms in noisy datasets. However, specific algorithms may outperform the consensus tree strategy in specific imaging conditions. Finally, to aid users in predicting the most accurate automatic tracing results without manual annotations for comparison, we used support vector machine regression to predict reconstruction quality given an image volume and a set of automatic tracings. This resource describes a collection of neurons from a variety of light microscopy-based datasets, which can serve as a gold standard for testing automated tracing algorithms, as shown by comparison of the performance of 35 algorithms.

Digital reconstructions provide an accurate and reliable way to store, share, model, quantify, and analyze neural morphology. Continuous advances in cellular labeling, tissue processing, microscopic imaging, and automated tracing catalyzed a proliferation of software applications to reconstruct neural morphology. These computer programs typically encode the data in custom file formats. The resulting format heterogeneity severely hampers the interoperability and reusability of these valuable data. Among these many alternatives, the SWC file format has emerged as a popular community choice, coalescing a rich ecosystem of related neuroinformatics resources for tracing, visualization, analysis, and simulation. This report presents a standardized specification of the SWC file format. Additionally, we introduce xyz2swc, a free online service that converts all 23 reconstruction formats (and 68 variations) described in the scientific literature into the SWC standard. The xyz2swc service is available open source through a user-friendly browser interface (https://neuromorpho.org/xyz2swc/ui/) and an Application Programming Interface (API).

Dendritic morphology underlies the source and processing of neuronal signal inputs. Morphology can be broadly described by two types of geometric characteristics. The first is dendrogram topology, defined by the length and frequency of the arbor branches; the second is spatial embedding, mainly determined by branch angles and tortuosity. We have previously demonstrated that microtubules and actin filaments are associated with arbor elongation and branching, fully constraining dendrogram topology. Here we relate the local distribution of these two primary cytoskeletal components with dendritic spatial embedding. We first reconstruct and analyze 167 sensory neurons from theDrosophilalarva encompassing multiple cell classes and genotypes. We observe that branches with higher microtubule concentration are overall straighter and tend to deviate less from the direction of their parent branch. F-actin displays a similar effect on the angular deviation from the parent branch direction, but its influence on branch tortuosity varies by class and genotype. We then create a computational model of dendritic morphology purely constrained by the cytoskeletal composition imaged from real neurons. The model quantitatively captures both spatial embedding and dendrogram topology across all tested neuron groups. These results suggest a common developmental mechanism regulating diverse morphologies, where the local cytoskeletal distribution can fully specify the overall emergent geometry of dendritic arbors.

Dendrites are the primary points of sensory or synaptic inputs to a neuron and play an essential role in synaptic integration and neural function. Despite the functional importance of dendrites, relatively less is known about the underlying mechanisms regulating cell-type specific dendritic patterning. Herein, we have dissected functional roles of a previously uncharacterized gene,CG3995, in cell-type specific dendritic development inDrosophila melanogaster.CG3995, which we have namedbedwarfed(bdwf), encodes a zinc-finger BED-type protein which is required for proportional growth and branching of dendritic arbors, exhibits nucleocytoplasmic expression, and functions in both transcriptional and translational cellular pathways. At the transcriptional level, we demonstrate a reciprocal regulatory relationship between Bdwf and the homeodomain transcription factor (TF) Cut. We show that Cut positively regulates Bdwf expression and that Bdwf acts as a downstream effector of Cut-mediated dendritic development, whereas overexpression of Bdwf negatively regulates Cut expression in multidendritic sensory neurons. Proteomic analyses revealed that Bdwf interacts with ribosomal proteins and disruption of these proteins produced phenotypically similar dendritic hypotrophy defects as observed inbdwfmutant neurons. We further demonstrate that Bdwf and its ribosomal protein interactors are required for normal microtubule and F-actin cytoskeletal architecture. Finally, our findings reveal that Bdwf is required to promote protein translation and ribosome trafficking along the dendritic arbor. Taken together, these results provide new insights into the complex, combinatorial and multi-functional roles of transcription factors (TFs) in directing diversification of cell-type specific dendritic development.

BigNeuron is an open community bench-testing platform combining the expertise of neuroscientists and computer scientists toward the goal of setting open standards for accurate and fast automatic neuron reconstruction. The project gathered a diverse set of image volumes across several species representative of the data obtained in most neuroscience laboratories interested in neuron reconstruction. Here we report generated gold standard manual annotations for a selected subset of the available imaging datasets and quantified reconstruction quality for 35 automatic reconstruction algorithms. Together with image quality features, the data were pooled in an interactive web application that allows users and developers to perform principal component analysis, t-distributed stochastic neighbor embedding, correlation and clustering, visualization of imaging and reconstruction data, and benchmarking of automatic reconstruction algorithms in user-defined data subsets. Our results show that image quality metrics explain most of the variance in the data, followed by neuromorphological features related to neuron size. By benchmarking automatic reconstruction algorithms, we observed that diverse algorithms can provide complementary information toward obtaining accurate results and developed a novel algorithm to iteratively combine methods and generate consensus reconstructions. The consensus trees obtained provide estimates of the neuron structure ground truth that typically outperform single algorithms. Finally, to aid users in predicting the most accurate automatic reconstruction results without manual annotations for comparison, we used support vector machine regression to predict reconstruction quality given an image volume and a set of automatic reconstructions.

Dendritic morphology underlies the source and processing of neuronal signal inputs. Morphology can be broadly described by two types of geometric characteristics. The first is dendrogram topology, defined by the length and frequency of the arbor branches; the second is spatial embedding, mainly determined by branch angles and straightness. We have previously demonstrated that microtubules and actin filaments are associated with arbor elongation and branching, fully constraining dendrogram topology. Here, we relate the local distribution of these two primary cytoskeletal components with dendritic spatial embedding. We first reconstruct and analyze 167 sensory neurons from the Drosophila larva encompassing multiple cell classes and genotypes. We observe that branches with a higher microtubule concentration tend to deviate less from the direction of their parent branch across all neuron types. Higher microtubule branches are also overall straighter. F-actin displays a similar effect on angular deviation and branch straightness, but not as consistently across all neuron types as microtubule. These observations raise the question as to whether the associations between cytoskeletal distributions and arbor geometry are sufficient constraints to reproduce type-specific dendritic architecture. Therefore, we create a computational model of dendritic morphology purely constrained by the cytoskeletal composition measured from real neurons. The model quantitatively captures both spatial embedding and dendrogram topology across all tested neuron groups. These results suggest a common developmental mechanism regulating diverse morphologies, where the local cytoskeletal distribution can fully specify the overall emergent geometry of dendritic arbors.

Dendrite shape impacts functional connectivity and is mediated by organization and dynamics of cytoskeletal fibers. Identifying the molecular factors that regulate dendritic cytoskeletal architecture is therefore important in understanding the mechanistic links between cytoskeletal organization and neuronal function. We identified Formin 3 (Form3) as an essential regulator of cytoskeletal architecture in nociceptive sensory neurons in Drosophila larvae. Time course analyses reveal that Form3 is cell-autonomously required to promote dendritic arbor complexity. We show that form3 is required for the maintenance of a population of stable dendritic microtubules (MTs), and mutants exhibit defects in the localization of dendritic mitochondria, satellite Golgi, and the TRPA channel Painless. Form3 directly interacts with MTs via FH1-FH2 domains. Mutations in human inverted formin 2 (INF2; ortholog of form3) have been causally linked to Charcot–Marie–Tooth (CMT) disease. CMT sensory neuropathies lead to impaired peripheral sensitivity. Defects in form3 function in nociceptive neurons result in severe impairment of noxious heat-evoked behaviors. Expression of the INF2 FH1-FH2 domains partially recovers form3 defects in MTs and nocifensive behavior, suggesting conserved functions, thereby providing putative mechanistic insights into potential etiologies of CMT sensory neuropathies.

Summary We describe how to reconstruct and quantify multi-signal neuronal morphology, using the dendritic distributions of microtubules and F-actin in sensory neurons from fly larvae as examples. We then provide a detailed procedure to analyze channel-specific morphometrics from these enhanced reconstructions. To illustrate applications, we demonstrate how to run a cytoskeleton-constrained simulation of dendritic tree generation and explain its validation against experimental data. This protocol is applicable to any species, developmental stage, brain region, cell class, branching process, and signal type. For complete details on the use and execution of this protocol, please refer to Nanda et al. (2020)., Graphical abstract, Highlights • A protocol to trace and produce multi-signal neural reconstructions • Quantification of multi-signal data, with a focus on cytoskeletal morphometrics • Simulation of virtual dendritic arbor, constrained by local cytoskeletal composition, We describe how to reconstruct and quantify multi-signal neuronal morphology, using the dendritic distributions of microtubules and F-actin in sensory neurons from fly larvae as examples. We then provide a detailed procedure to analyze channel-specific morphometrics from these enhanced reconstructions. To illustrate applications, we demonstrate how to run a cytoskeleton-constrained simulation of dendritic tree generation and explain its validation against experimental data. This protocol is applicable to any species, developmental stage, brain region, cell class, branching process, and signal type.

Transcription factors (TFs) have emerged as essential cell autonomous mediators of subtype specific dendritogenesis; however, the downstream effectors of these TFs remain largely unknown, as are the cellular events that TFs control to direct morphological change. As dendritic morphology is largely dictated by the organization of the actin and microtubule (MT) cytoskeletons, elucidating TF-mediated cytoskeletal regulatory programs is key to understanding molecular control of diverse dendritic morphologies. Previous studies in Drosophila melanogaster have demonstrated that the conserved TFs Cut and Knot exert combinatorial control over aspects of dendritic cytoskeleton development, promoting actin and MT-based arbor morphology, respectively. To investigate transcriptional targets of Cut and/or Knot regulation, we conducted systematic neurogenomic studies, coupled with in vivo genetic screens utilizing multi-fluor cytoskeletal and membrane marker reporters. These analyses identified a host of putative Cut and/or Knot effector molecules, and a subset of these putative TF targets converge on modulating dendritic cytoskeletal architecture, which are grouped into three major phenotypic categories, based upon neuromorphometric analyses: complexity enhancer, complexity shifter, and complexity suppressor. Complexity enhancer genes normally function to promote higher order dendritic growth and branching with variable effects on MT stabilization and F-actin organization, whereas complexity shifter and complexity suppressor genes normally function in regulating proximal-distal branching distribution or in restricting higher order branching complexity, respectively, with spatially restricted impacts on the dendritic cytoskeleton. Collectively, we implicate novel genes and cellular programs by which TFs distinctly and combinatorially govern dendritogenesis via cytoskeletal modulation.

Summary Microtubules (MTs) and F-actin (F-act) have long been recognized as key regulators of dendritic morphology. Nevertheless, precisely ascertaining their distinct influences on dendritic trees have been hampered until now by the lack of direct, arbor-wide cytoskeletal quantification. We pair live confocal imaging of fluorescently labeled dendritic arborization (da) neurons in Drosophila larvae with complete multi-signal neural tracing to separately measure MTs and F-act. We demonstrate that dendritic arbor length is highly interrelated with local MT quantity, whereas local F-act enrichment is associated with dendritic branching. Computational simulation of arbor structure solely constrained by experimentally observed subcellular distributions of these cytoskeletal components generated synthetic morphological and molecular patterns statistically equivalent to those of real da neurons, corroborating the efficacy of local MT and F-act in describing dendritic architecture. The analysis and modeling outcomes hold true for the simplest (class I), most complex (class IV), and genetically altered (Formin3 overexpression) da neuron types., Graphical Abstract, Highlights • Local microtubule quantity is highly interrelated with arbor length • Bifurcations are strongly associated with enrichment in local F-actin • A model based on local microtubule and F-actin reproduces dendritic morphology • The above findings are robust across cell types and genetic alterations, Biological Sciences; Molecular Biology; Neuroscience; Cell Biology

NeuroMorpho.Org was launched in 2006 to provide unhindered access to any and all digital tracings of neuronal morphology that researchers were willing to share freely upon request. Today this database is the largest public inventory of cellular reconstructions in neuroscience with a content of over 80,000 neurons and glia from a representative diversity of animal species, anatomical regions, and experimental methods. Datasets continuously contributed by hundreds of laboratories worldwide are centrally curated, converted into a common non-proprietary format, morphometrically quantified, and annotated with comprehensive metadata. Users download digital reconstructions for a variety of scientific applications including visualization, classification, analysis, and simulations. With more than 1,000 peer-reviewed publications describing data stored in or utilizing data retrieved from NeuroMorpho.Org, this ever-growing repository can already be considered a mature resource for neuroscience.

Several efficient procedures exist to digitally trace neuronal structure from light microscopy, and mature community resources have emerged to store, share, and analyze these datasets. In contrast, the quantification of intracellular distributions and morphological dynamics is not yet standardized. Current widespread descriptions of neuron morphology are static and inadequate for subcellular characterizations. We introduce a new file format to represent multichannel information as well as an open-source Vaa3D plugin to acquire this type of data. Next we define a novel data structure to capture morphological dynamics, and demonstrate its application to different time-lapse experiments. Importantly, we designed both innovations as judicious extensions of the classic SWC format, thus ensuring full back-compatibility with popular visualization and modeling tools. We then deploy the combined multichannel/time-varying reconstruction system on developing neurons in live Drosophila larvae by digitally tracing fluorescently labeled cytoskeletal components along with overall dendritic morphology as they changed over time. This same design is also suitable for quantifying dendritic calcium dynamics and tracking arbor-wide movement of any subcellular substrate of interest.

The acquisition, maintenance and modulation of dendritic architecture are critical to neuronal form, plasticity and function. Morphologically, dendritic shape impacts functional connectivity and is largely mediated by organization and dynamics of cytoskeletal fibers that provide the underlying scaffold and tracks for intracellular trafficking. Identifying molecular factors that regulate dendritic cytoskeletal architecture is therefore important in understanding mechanistic links between cytoskeletal organization and neuronal function. In a neurogenomic-driven genetic screen of cytoskeletal regulatory molecules, we identified Formin3 (Form3) as a critical regulator of cytoskeletal architecture in Drosophila nociceptive sensory neurons. Form3 is a member of the conserved Formin family of multi-functional cytoskeletal regulators and time course analyses reveal Form3 is cell-autonomously required for maintenance of complex dendritic arbors. Cytoskeletal imaging demonstrates form3 mutants exhibit a specific destabilization of the dendritic microtubule (MT) cytoskeleton, together with defective dendritic trafficking of mitochondria, satellite Golgi and the TRPA channel Painless. Biochemical studies reveal Form3 directly interacts with MTs via FH1-FH2 domains and promotes MT stabilization via acetylation. Neurologically, mutations in human Inverted Formin 2 (INF2; ortholog of form3) have been causally linked to Charcot-Marie-Tooth (CMT) disease. CMT sensory neuropathies lead to impaired peripheral sensitivity. Defects in form3 function in nociceptive neurons results in a severe impairment in noxious heat evoked behaviors. Expression of the INF2 FH1-FH2 domains rescues form3 defects in MT stabilization and nocifensive behavior revealing conserved functions in regulating the cytoskeleton and sensory behavior thereby providing novel mechanistic insights into potential etiologies of CMT sensory neuropathies.Significance StatementMechanisms governing cytoskeletal architecture are critical in regulating neural function as aberrations are linked to a broad spectrum of neurological and neurocognitive disorders. Formins are important cytoskeletal regulators however their mechanistic roles in neuronal architecture are poorly understood. We demonstrate mutations in Drosophila formin3 lead to progressive destabilization of the dendritic microtubule cytoskeleton resulting in severely reduced arborization coupled to impaired organelle and ion channel trafficking, as well as nociceptive sensitivity. INF2 mutations are implicated in CMT sensory neuropathies, and INF2 expression can rescue microtubule and nociceptive behavioral defects in form3 mutants. While CMT sensory neuropathies have been linked to defects in axonal development and myelination, our studies connect dendritic cytoskeletal defects with peripheral insensitivity suggesting possible alternative etiological bases.

Pairing in vivo imaging and computational modeling of dendritic arborization (da) neurons from the fruit fly larva provides a unique window into neuronal growth and underlying molecular processes. We image, reconstruct, and analyze the morphology of wild-type, RNAi-silenced, and mutant da neurons. We then use local and global rule-based stochastic simulations to generate artificial arbors, and identify the parameters that statistically best approximate the real data. We observe structural homeostasis in all da classes, where an increase in size of one dendritic stem is compensated by a reduction in the other stems of the same neuron. Local rule models show that bifurcation probability is determined by branch order, while branch length depends on path distance from the soma. Global rule simulations suggest that most complex morphologies tend to be constrained by resource optimization, while simpler neuron classes privilege path distance conservation. Genetic manipulations affect both the local and global optimal parameters, demonstrating functional perturbations in growth mechanisms.

In this Commentary, Ascoli et al. discuss recipes for setting up public data sharing initiatives based on their experiences with NeuroMorpho.Org. Most neuroscientists have yet to embrace a culture of data sharing. Using our decade-long experience at NeuroMorpho.Org as an example, we discuss how publicly available repositories may benefit data producers and end-users alike. We outline practical recipes for resource developers to maximize the research impact of data sharing platforms for both contributors and users.

Mature dendritic arbors emerge out of complex growth mechanisms involving intracellular, extracellular, and activity-dependent factors. These interactions converge on cytoskeletal effectors, mainly microtubules and actin filaments, which mediate the structural changes and stabilize the mature structure. The quantitative characterization of developmental dynamics remains challenging because current morphological descriptors are static and without explicit representation of subcellular composition. Large datasets of new time-varying reconstructions with co-registered internal cytoskeletal information are required to build statistically reliable models of dendritic growth and plasticity. Here we review the history and current state of experimental and theoretical approaches, and illustrate the progress of an innovative closed-loop research design using the Drosophila larva system. Time-lapse confocal images of the fluorescently labeled cytoskeletal components are digitally reconstructed into a novel file structure, enabling comprehensive statistical analysis and data-driven computational simulations of dendritic growth. These data in turn guide the most informative genetic manipulations for testing specific hypotheses.

NeuroMorpho.Org is a centralized repository of neuronal reconstructions hosting data from a variety of species, brain regions, and experimental conditions1. This resource aims to provide dense coverage of available data by including all digital tracings described in peer-reviewed publications that the authors are willing to share2. Although most reconstructions to date are acquired manually or semi-manually3, the transition to quasi-automated methods is widely considered as necessary for long-term progress4. The 2010 DIADEM competition (DiademChallenge.org) helped foster considerable advances towards tracing automation5 and was followed one year later by the large-scale reconstruction of more than 16,000 Drosophila neurons6. The public posting of all image stacks and corresponding digital tracings on flycircuit.tw after an additional year7 constituted the first (and so far only) success in high-throughput digital morphology. Although flycircuit.tw reconstructions are beginning to enable new analysis and discoveries by independent research groups8, these data were posted in a commercial format (vsg3d.com/amira/skeletonization) and lacked useful information such as the somatic brain region. Following the open invitation of flycircuit.tw to copy, transform, and redistribute the material for non-commercial re-use, here we announce inclusion of this dataset in non-proprietary SWC format, along with additional metadata and morphometric measurements, under “Chiang archive” in NeuroMorpho.Org version 6.0. With this major release, the number of NeuroMorpho.Org reconstructions more than doubles from 11,335 to 27,385.