Early morphological and neurochemical changes of the bed nucleus of stria terminalis (BNST) in gestational protein-restricted male offspring

BACKGROUND

The bed nucleus of the stria terminalis (BNST) is a structure with a peculiar neurochemical composition involved in modulating anxietylike behavior and fear.

AIM

The present study investigated the effects on the BNST neurochemical composition and neuronal structure in critical moments of the postnatal period in gestational protein-restricted male rats' offspring.

METHODS

Dams were maintained during the pregnancy on isocaloric rodent laboratory chow with standard protein content [NP, 17%] or low protein content [LP, 6%]. BNST from male NP and age-matched LP offspring was studied using the isotropic fractionator method, Neuronal 3D reconstruction, dendritic-tree analysis, blotting analysis, and high-performance liquid chromatography.

RESULTS

Serum corticosterone levels were higher in male LP offspring than NP rats in 14-day-old offspring, without any difference in 7-day-old progeny. The BNST total cell number and anterodorsal BNST division volume in LP progeny were significantly reduced on the 14th postnatal day compared with NP offspring. The BNST HPLC analysis from 7 days-old LP revealed increased norepinephrine levels compared to NP progeny. The BNST blot analysis from 7-day-old LP revealed reduced levels of GR and BDNF associated with enhanced CRF1 expression compared to NP offspring. 14-day-old LP offspring showed reduced expression of MR and 5HT1A associated with decreased DOPAC and DOPA turnover levels relative to NP rats. In Conclusion, the BNST cellular and neurochemical changes may represent adaptation during development in response to elevated fetal exposure to maternal corticosteroid levels. In this way, gestational malnutrition alters the BNST content and structure and contributes to already-known behavioral changes.

NeuroEditor: a tool to edit and visualize neuronal morphologies

The digital extraction of detailed neuronal morphologies from microscopy data is an essential step in the study of neurons. Ever since Cajal's work, the acquisition and analysis of neuron anatomy has yielded invaluable insight into the nervous system, which has led to our present understanding of many structural and functional aspects of the brain and the nervous system, well beyond the anatomical perspective. Obtaining detailed anatomical data, though, is not a simple task. Despite recent progress, acquiring neuron details still involves using labor-intensive, error prone methods that facilitate the introduction of inaccuracies and mistakes. In consequence, getting reliable morphological tracings usually needs the completion of post-processing steps that require user intervention to ensure the extracted data accuracy. Within this framework, this paper presents NeuroEditor, a new software tool for visualization, editing and correction of previously reconstructed neuronal tracings. This tool has been developed specifically for alleviating the burden associated with the acquisition of detailed morphologies. NeuroEditor offers a set of algorithms that can automatically detect the presence of potential errors in tracings. The tool facilitates users to explore an error with a simple mouse click so that it can be corrected manually or, where applicable, automatically. In some cases, this tool can also propose a set of actions to automatically correct a particular type of error. Additionally, this tool allows users to visualize and compare the original and modified tracings, also providing a 3D mesh that approximates the neuronal membrane. The approximation of this mesh is computed and recomputed on-the-fly, reflecting any instantaneous changes during the tracing process. Moreover, NeuroEditor can be easily extended by users, who can program their own algorithms in Python and run them within the tool. Last, this paper includes an example showing how users can easily define a customized workflow by applying a sequence of editing operations. The edited morphology can then be stored, together with the corresponding 3D mesh that approximates the neuronal membrane.

Gestational protein restriction alters early amygdala neurochemistry in male offspring

BACKGROUND

Gestational protein intake restriction-induced long-lasting harmful outcomes in the offspring's organs and systems. However, few studies have focused on this event's impact on the brain's structures and neurochemical compounds.

AIM

The present study investigated the effects on the amygdala neurochemical composition and neuronal structure in gestational protein-restricted male rats' offspring.

METHODS

Dams were maintained on isocaloric standard rodent laboratory chow with regular protein [NP, 17%] or low protein content [LP, 6%]. Total cells were quantified using the Isotropic fractionator method, Neuronal 3D reconstruction, and dendritic tree analysis using the Golgi-Cox technique. Western blot and high-performance liquid chromatography performed neurochemical studies.

RESULTS

The gestational low-protein feeding offspring showed a significant decrease in birth weight up to day 14, associated with unaltered brain weight in youth or adult progenies. The amygdala cell numbers were unchanged, and the dendrites length and dendritic ramifications 3D analysis in LP compared to age-matched NP progeny. However, the current study shows reduced amygdala content of norepinephrine, epinephrine, and dopamine in LP progeny. These offspring observed a significant reduction in the amygdala glucocorticoid (GR) and mineralocorticoid (MR) receptor protein levels. Also corticotrophin-releasing factor (CRF) amygdala protein content was reduced in 7 and 14-day-old LP rats.

CONCLUSION

The observed amygdala neurochemical changes may represent adaptation during embryonic development in response to elevated fetal exposure to maternal corticosteroid levels. In this way, gestational malnutrition stress can alter the amygdala's neurochemical content and may contribute to known behavioral changes induced by gestational protein restriction.

Neuronal branching is increasingly asymmetric near synapses, potentially enabling plasticity while minimizing energy dissipation and conduction time

Neurons' primary function is to encode and transmit information in the brain and body. The branching architecture of axons and dendrites must compute, respond and make decisions while obeying the rules of the substrate in which they are enmeshed. Thus, it is important to delineate and understand the principles that govern these branching patterns. Here, we present evidence that asymmetric branching is a key factor in understanding the functional properties of neurons. First, we derive novel predictions for asymmetric scaling exponents that encapsulate branching architecture associated with crucial principles such as conduction time, power minimization and material costs. We compare our predictions with extensive data extracted from images to associate specific principles with specific biophysical functions and cell types. Notably, we find that asymmetric branching models lead to predictions and empirical findings that correspond to different weightings of the importance of maximum, minimum or total path lengths from the soma to the synapses. These different path lengths quantitatively and qualitatively affect energy, time and materials. Moreover, we generally observe that higher degrees of asymmetric branching-potentially arising from extrinsic environmental cues and synaptic plasticity in response to activity-occur closer to the tips than the soma (cell body).

Local Microtubule and F-Actin Distributions Fully Constrain the Spatial Geometry of Drosophila Sensory Dendritic Arbors

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.

p120-catenin subfamily members have distinct as well as shared effects on dendrite morphology during neuron development in vitro

Dendritic arborization is essential for proper neuronal connectivity and function. Conversely, abnormal dendrite morphology is associated with several neurological pathologies like Alzheimer's disease and schizophrenia. Among major intrinsic mechanisms that determine the extent of the dendritic arbor is cytoskeletal remodeling. Here, we characterize and compare the impact of the four proteins involved in cytoskeletal remodeling-vertebrate members of the p120-catenin subfamily-on neuronal dendrite morphology. In relation to each of their own distributions, we find that p120-catenin and delta-catenin are expressed at relatively higher proportions in growth cones compared to ARVCF-catenin and p0071-catenin; ARVCF-catenin is expressed at relatively high proportions in the nucleus; and all catenins are expressed in dendritic processes and the soma. Through altering the expression of each p120-subfamily catenin in neurons, we find that exogenous expression of either p120-catenin or delta-catenin correlates with increased dendritic length and branching, whereas their respective depletion decreases dendritic length and branching. While increasing ARVCF-catenin expression also increases dendritic length and branching, decreasing expression has no grossly observable morphological effect. Finally, increasing p0071-catenin expression increases dendritic branching, but not length, while decreasing expression decreases dendritic length and branching. These distinct localization patterns and morphological effects during neuron development suggest that these catenins have both shared and distinct roles in the context of dendrite morphogenesis.

The impact of neuron morphology on cortical network architecture

The neurons in the cerebral cortex are not randomly interconnected. This specificity in wiring can result from synapse formation mechanisms that connect neurons, depending on their electrical activity and genetically defined identity. Here, we report that the morphological properties of the neurons provide an additional prominent source by which wiring specificity emerges in cortical networks. This morphologically determined wiring specificity reflects similarities between the neurons’ axo-dendritic projections patterns, the packing density, and the cellular diversity of the neuropil. The higher these three factors are, the more recurrent is the topology of the network. Conversely, the lower these factors are, the more feedforward is the network’s topology. These principles predict the empirically observed occurrences of clusters of synapses, cell type-specific connectivity patterns, and nonrandom network motifs. Thus, we demonstrate that wiring specificity emerges in the cerebral cortex at subcellular, cellular, and network scales from the specific morphological properties of its neuronal constituents.

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Neuronal network architectures reflect the morphologies of their constituents

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Morphology predicts nonrandom connectivity from subcellular to network scales

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Morphology predicts connectivity patterns consistent with those observed empirically

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Neuron morphology is a major source for wiring specificity in the cerebral cortex

Comparative neuropathology in aging primates: A perspective

While humans exhibit a significant degree of neuropathological changes associated with deficits in cognitive and memory functions during aging, non-human primates (NHP) present with more variable expressions of pathological alterations among individuals and species. As such, NHP with long life expectancy in captivity offer an opportunity to study brain senescence in the absence of the typical cellular pathology caused by age-related neurodegenerative illnesses commonly seen in humans. Age-related changes at neuronal population, single cell, and synaptic levels have been well documented in macaques and marmosets, while age-related and Alzheimer's disease-like neuropathology has been characterized in additional species including lemurs as well as great apes. We present a comparative overview of existing neuropathologic observations across the primate order, including classic age-related changes such as cell loss, amyloid deposition, amyloid angiopathy, and tau accumulation. We also review existing cellular and ultrastructural data on neuronal changes, such as dendritic attrition and spine alterations, synaptic loss and pathology, and axonal and myelin pathology, and discuss their repercussions on cellular and systems function and cognition.

Altered White Matter and Layer VIb Neurons in Heterozygous Disc1 Mutant, a Mouse Model of Schizophrenia

Increased white matter neuron density has been associated with neuropsychiatric disorders including schizophrenia. However, the pathogenic features of these neurons are still largely unknown. Subplate neurons, the earliest generated neurons in the developing cortex have also been associated with schizophrenia and autism. The link between these neurons and mental disorders is also not well established. Since cortical layer VIb neurons are believed to be the remnant of subplate neurons in the adult rodent brain, in this study, we aimed to examine the cytoarchitecture of neurons in cortical layer VIb and the underlying white matter in heterozygous Disc1 mutant (Het) mice, a mouse model of schizophrenia. In the white matter, the number of NeuN-positive neurons was quite low in the external capsule; however, the density of these cells was found increased (54%) in Het mice compared with wildtype (WT) littermates. The density of PV-positive neurons was unchanged in the mutants. In the cortical layer VIb, the density of CTGF-positive neurons increased (21.5%) in Het mice, whereas the number of Cplx3-positive cells reduced (16.1%) in these mutants, compared with WT mice. Layer VIb neurons can be classified by their morphological characters. The morphology of Type I pyramidal neurons was comparable between genotypes while the dendritic length and complexity of Type II multipolar neurons were significantly reduced in Het mice. White matter neurons and layer VIb neurons receive synaptic inputs and modulate the process of sensory information and sleep/arousal pattern. Aberrances of these neurons in Disc1 mutants implies altered brain functions in these mice.

Prenatal music exposure influences weight, ghrelin expression, and morphology of rat hypothalamic neuron cultures

Music plays an important role in brain physiology, in some areas related to emotions, food intake and body weight, such as the hypothalamus. There are different frequencies to which it can be tuned, today the most utilized is at 440 Hz, while in the past the 432 Hz frequency was more used to show particular effects on brain. It is known that Ghrelin, a peptide hormone, regulates food intake in the hypothalamus; in a previous paper, we reported that musical stimuli at 432 Hz modified the Ghrelin expression in the rat, increasing beneficial effects on metabolism. In this study, we used this frequency and we focused our attention on body weight, Ghrelin expression, and neuron morphology in hypothalamic cultures. To investigate the role of music, we utilized newborn pups from pregnant rats that were exposed to music stimuli at 432 Hz during the perinatal period and for the postnatal period, some for 3 days (P3) and others for 6 days (P6). Some pups were not exposed to music stimuli (controls). Our results showed that music increased the body weight of pups; in addition, enhanced Ghrelin expression in hypothalamic neurons and their axonal elongation were highlighted by immunocytochemical techniques. Moreover, we found that the positive music effect started in pups at P3 and increased at P6 compared with controls. These results suggest that the musical frequency at 432 Hz could stimulate the orexigenic Ghrelin effects influencing the increase in body weight and affecting the number of hypothalamic neurons expressing Ghrelin.

Neuronize v2: Bridging the Gap Between Existing Proprietary Tools to Optimize Neuroscientific Workflows

Knowledge about neuron morphology is key to understanding brain structure and function. There are a variety of software tools that are used to segment and trace the neuron morphology. However, these tools usually utilize proprietary formats. This causes interoperability problems since the information extracted with one tool cannot be used in other tools. This article aims to improve neuronal reconstruction workflows by facilitating the interoperability between two of the most commonly used software tools—Neurolucida (NL) and Imaris (Filament Tracer). The new functionality has been included in an existing tool—Neuronize—giving rise to its second version. Neuronize v2 makes it possible to automatically use the data extracted with Imaris Filament Tracer to generate a tracing with dendritic spine information that can be read directly by NL. It also includes some other new features, such as the ability to unify and/or correct inaccurately-formed meshes (i.e., dendritic spines) and to calculate new metrics. This tool greatly facilitates the process of neuronal reconstruction, bridging the gap between existing proprietary tools to optimize neuroscientific workflows.

The X-Linked Intellectual Disability Gene Zdhhc9 Is Essential for Dendrite Outgrowth and Inhibitory Synapse Formation

Palmitoylation is a reversible post-translational lipid modification that facilitates vesicular transport and subcellular localization of modified proteins. This process is catalyzed by ZDHHC enzymes that are implicated in several neurological and neurodevelopmental disorders. Loss-of-function mutations in ZDHHC9 have been identified in patients with X-linked intellectual disability (XLID) and associated with increased epilepsy risk. Loss of Zdhhc9 function in hippocampal cultures leads to shorter dendritic arbors and fewer inhibitory synapses, altering the ratio of excitatory-to-inhibitory inputs formed onto Zdhhc9-deficient cells. While Zdhhc9 promotes dendrite outgrowth through the palmitoylation of the GTPase Ras, it promotes inhibitory synapse formation through the palmitoylation of another GTPase, TC10. Zdhhc9 knockout mice exhibit seizure-like activity together with increased frequency and amplitude of both spontaneous and miniature excitatory and inhibitory postsynaptic currents. These findings present a plausible mechanism for how the loss of ZDHHC9 function may contribute to XLID and epilepsy.

Transgenic Cross-Referencing of Inhibitory and Excitatory Interneuron Populations to Dissect Neuronal Heterogeneity in the Dorsal Horn

The superficial dorsal horn (SDH, LI-II) of the spinal cord receives and processes multimodal sensory information from skin, muscle, joints, and viscera then relay it to the brain. Neurons within the SDH fall into two broad categories, projection neurons and interneurons. The later can be further subdivided into excitatory and inhibitory types. Traditionally, interneurons within the SDH have been divided into overlapping groups according to their neurochemical, morphological and electrophysiological properties. Recent clustering analyses, based on molecular transcript profiles of cells and nuclei, have predicted many more functional groups of interneurons than expected using traditional approaches. In this study, we used electrophysiological and morphological data obtained from genetically-identified excitatory (vGLUT2) and inhibitory (vGAT) interneurons in transgenic mice to cluster cells into groups sharing common characteristics and subsequently determined how many clusters can be assigned by combinations of these properties. Consistent with previous reports, we show differences exist between excitatory and inhibitory interneurons in terms of their excitability, nature of the ongoing excitatory drive, action potential (AP) properties, sub-threshold current kinetics, and morphology. The resulting clusters based on statistical and unbiased assortment of these data fell well short of the numbers of molecularly predicted clusters. There was no clear characteristic that in isolation defined a population, rather multiple variables were needed to predict cluster membership. Importantly though, our analysis highlighted the appropriateness of using transgenic lines as tools to functionally subdivide both excitatory and inhibitory interneuron populations.

ShuTu: Open-Source Software for Efficient and Accurate Reconstruction of Dendritic Morphology

Neurons perform computations by integrating inputs from thousands of synapses-mostly in the dendritic tree-to drive action potential firing in the axon. One fruitful approach to studying this process is to record from neurons using patch-clamp electrodes, fill the recorded neurons with a substance that allows subsequent staining, reconstruct the three-dimensional architectures of the dendrites, and use the resulting functional and structural data to develop computer models of dendritic integration. Accurately producing quantitative reconstructions of dendrites is typically a tedious process taking many hours of manual inspection and measurement. Here we present ShuTu, a new software package that facilitates accurate and efficient reconstruction of dendrites imaged using bright-field microscopy. The program operates in two steps: (1) automated identification of dendritic processes, and (2) manual correction of errors in the automated reconstruction. This approach allows neurons with complex dendritic morphologies to be reconstructed rapidly and efficiently, thus facilitating the use of computer models to study dendritic structure-function relationships and the computations performed by single neurons.

Adaptations during Maturation in an Identified Honeybee Interneuron Responsive to Waggle Dance Vibration Signals

Honeybees are social insects, and individual bees take on different social roles as they mature, performing a multitude of tasks that involve multi-modal sensory integration. Several activities vital for foraging, like flight and waggle dance communication, involve sensing air vibrations through their antennae. We investigated changes in the identified vibration-sensitive interneuron DL-Int-1 in the honeybee Apis mellifera during maturation by comparing properties of neurons from newly emerged adult and forager honeybees. Although comparison of morphological reconstructions of the neurons revealed no significant changes in gross dendritic features, consistent and region-dependent changes were found in dendritic density. Comparison of electrophysiological properties showed an increase in the firing rate differences between stimulus and nonstimulus periods in foragers compared with newly emerged adult bees. The observed differences in neurons of foragers compared with newly emerged adult honeybees suggest refined connectivity, improved signal propagation, and enhancement of response features possibly important for the network processing of air vibration signals relevant for the waggle dance communication of honeybees.

LIMK2-1 is a Hominidae-Specific Isoform of LIMK2 Expressed in Central Nervous System and Associated with Intellectual Disability

LIMK2 is involved in neuronal functions by regulating actin dynamics. Different isoforms of LIMK2 are described in databanks. LIMK2a and LIMK2b are the most characterized. A few pieces of evidence suggest that LIMK2 isoforms might not have overlapping functions. In this study, we focused our attention on a less studied human LIMK2 isoform, LIMK2-1. Compared to the other LIMK2 isoforms, LIMK2-1 contains a supplementary C-terminal phosphatase 1 inhibitory domain (PP1i). We found out that this isoform was hominidae-specific and showed that it was expressed in human fetal brain and faintly in adult brain. Its coding sequence was sequenced in 173 patients with sporadic non-syndromic intellectual disability (ID), and we observed an association of a rare missense variant in the PP1i domain (rs151191437, p.S668P) with ID. Our results also suggest an implication of LIMK2-1 in neurite outgrowth and neurons arborization which appears to be affected by the p.S668P variation. Therefore our results suggest that LIMK2-1 plays a role in the developing brain, and that a rare variation of this isoform is a susceptibility factor in ID.

Mechanosensory Neuron Aging: Differential Trajectories with Lifespan-Extending Alaskan Berry and Fungal Treatments in Caenorhabditis elegans

Many nutritional interventions that increase lifespan are also proposed to postpone age-related declines in motor and cognitive function. Potential sources of anti-aging compounds are the plants and fungi that have adapted to extreme environments. We studied the effects of four commonly consumed and culturally relevant Interior Alaska berry and fungus species (bog blueberry, lowbush cranberry, crowberry, and chaga) on the decline in overall health and neuron function and changes in touch receptor neuron morphology associated with aging. We observed increased wild-type Caenorhabditis elegans lifespan and improved markers of healthspan upon treatment with Alaskan blueberry, lowbush cranberry, and chaga extracts. Interestingly, although all three treatments increased lifespan, they differentially affected the development of aberrant morphologies in touch receptor neurons. Blueberry treatments decreased anterior mechanosensory neuron (ALM) aberrations (i.e., extended outgrowths and abnormal cell bodies) while lowbush cranberry treatment increased posterior mechanosensory neuron (PLM) aberrations, namely process branching. Chaga treatment both decreased ALM aberrations (i.e., extended outgrowths) and increased PLM aberrations (i.e., process branching and loops). These results support the large body of knowledge positing that there are multiple cellular strategies and mechanisms for promoting health with age. Importantly, these results also demonstrate that although an accumulation of abnormal neuron morphologies is associated with aging and decreased health, not all of these morphologies are detrimental to neuronal and organismal health.

Microtubule nucleation and organization in dendrites

Dendrite branching is an essential process for building complex nervous systems. It determines the number, distribution and integration of inputs into a neuron, and is regulated to create the diverse dendrite arbor branching patterns characteristic of different neuron types. The microtubule cytoskeleton is critical to provide structure and exert force during dendrite branching. It also supports the functional requirements of dendrites, reflected by differential microtubule architectural organization between neuron types, illustrated here for sensory neurons. Both anterograde and retrograde microtubule polymerization occur within growing dendrites, and recent studies indicate that branching is enhanced by anterograde microtubule polymerization events in nascent branches. The polarities of microtubule polymerization events are regulated by the position and orientation of microtubule nucleation events in the dendrite arbor. Golgi outposts are a primary microtubule nucleation center in dendrites and share common nucleation machinery with the centrosome. In addition, pre-existing dendrite microtubules may act as nucleation sites. We discuss how balancing the activities of distinct nucleation machineries within the growing dendrite can alter microtubule polymerization polarity and dendrite branching, and how regulating this balance can generate neuron type-specific morphologies.

The effects of neuron morphology on graph theoretic measures of network connectivity: the analysis of a two-level statistical model

We developed a two-level statistical model that addresses the question of how properties of neurite morphology shape the large-scale network connectivity. We adopted a low-dimensional statistical description of neurites. From the neurite model description we derived the expected number of synapses, node degree, and the effective radius, the maximal distance between two neurons expected to form at least one synapse. We related these quantities to the network connectivity described using standard measures from graph theory, such as motif counts, clustering coefficient, minimal path length, and small-world coefficient. These measures are used in a neuroscience context to study phenomena from synaptic connectivity in the small neuronal networks to large scale functional connectivity in the cortex. For these measures we provide analytical solutions that clearly relate different model properties. Neurites that sparsely cover space lead to a small effective radius. If the effective radius is small compared to the overall neuron size the obtained networks share similarities with the uniform random networks as each neuron connects to a small number of distant neurons. Large neurites with densely packed branches lead to a large effective radius. If this effective radius is large compared to the neuron size, the obtained networks have many local connections. In between these extremes, the networks maximize the variability of connection repertoires. The presented approach connects the properties of neuron morphology with large scale network properties without requiring heavy simulations with many model parameters. The two-steps procedure provides an easier interpretation of the role of each modeled parameter. The model is flexible and each of its components can be further expanded. We identified a range of model parameters that maximizes variability in network connectivity, the property that might affect network capacity to exhibit different dynamical regimes.

Optimization of CLARITY for Clearing Whole-Brain and Other Intact Organs

CLARITY is a novel technique for optical clearance and intact imaging of biological specimens. This method was introduced in 2013 but has been difficult for some researchers to implement.

The development, refinement, and use of techniques that allow high-throughput imaging of whole brains with cellular resolution will help us understand the complex functions of the brain. Such techniques are crucial for the analysis of complete neuronal morphology—anatomical and functional—connectivity, and repeated molecular phenotyping. CLARITY is a recently introduced technique that produces structurally intact, yet optically transparent tissue, which may be labeled and imaged without sectioning. However, the utility of this technique depends on several procedural variables during the process in which the light-scattering lipids in a tissue are replaced by a transparent hydrogel matrix. Here, we systematically varied a number of factors (including temperature, hydrogel composition, and polymerization conditions) to provide an optimized, highly replicable CLARITY procedure for clearing mouse brains. We found that for these preparations optimal tissue clearing requires electrophoresis (and cannot be achieved with passive clearing alone) for 5 d with a combination of 37 and 55°C temperature. Although this protocol is optimized for brains, we also show that it can be used to clear and analyze a variety of organs. Brain or other tissue prepared using this protocol is suitable for high-throughput imaging with confocal or single-plane illumination microscopy.

Quantitative investigations of axonal and dendritic arbors: development, structure, function, and pathology

The branching structures of neurons are a long-standing focus of neuroscience. Axonal and dendritic morphology affect synaptic signaling, integration, and connectivity, and their diversity reflects the computational specialization of neural circuits. Altered neuronal morphology accompanies functional changes during development, experience, aging, and disease. Technological improvements continuously accelerate high-throughput tissue processing, image acquisition, and morphological reconstruction. Digital reconstructions of neuronal morphologies allow for complex quantitative analyses that are unattainable from raw images or two-dimensional tracings. Furthermore, digitized morphologies enable computational modeling of biophysically realistic neuronal dynamics. Additionally, reconstructions generated to address specific scientific questions have the potential for continued investigations beyond the original reason for their acquisition. Facilitating multiple reuse are repositories like NeuroMorpho.Org, which ease the sharing of reconstructions. Here, we review selected scientific literature reporting the reconstruction of axonal or dendritic morphology with diverse goals including establishment of neuronal identity, examination of physiological properties, and quantification of developmental or pathological changes. These reconstructions, deposited in NeuroMorpho.Org, have since been used by other investigators in additional research, of which we highlight representative examples. This cycle of data generation, analysis, sharing, and reuse reveals the vast potential of digital reconstructions in quantitative investigations of neuronal morphology.

The Caenorhabditis elegans microtubule minus-end binding homolog PTRN-1 stabilizes synapses and neurites

Microtubule dynamics facilitate neurite growth and establish morphology, but the role of minus-end binding proteins in these processes is largely unexplored. CAMSAP homologs associate with microtubule minus-ends, and are important for the stability of epithelial cell adhesions. In this study, we report morphological defects in neurons and neuromuscular defects in mutants of the C. elegans CAMSAP, ptrn-1. Mechanosensory neurons initially extend wild-type neurites, and subsequently remodel by overextending neurites and retracting synaptic branches and presynaptic varicosities. This neuronal remodeling can be activated by mutations known to alter microtubules, and depends on a functioning DLK-1 MAP kinase pathway. We found that PTRN-1 localizes to both neurites and synapses, and our results suggest that alterations of microtubule structures caused by loss of PTRN-1 function activates a remodeling program leading to changes in neurite morphology. We propose a model whereby minus-end microtubule stabilization mediated by a functional PTRN-1 is necessary for morphological maintenance of neurons. DOI: http://dx.doi.org/10.7554/eLife.01637.001.

Using diffusion anisotropy to characterize neuronal morphology in gray matter: the orientation distribution of axons and dendrites in the NeuroMorpho.org database

Accurate mathematical modeling is integral to the ability to interpret diffusion magnetic resonance (MR) imaging data in terms of cellular structure in brain gray matter (GM). In previous work, we derived expressions to facilitate the determination of the orientation distribution of axonal and dendritic processes from diffusion MR data. Here we utilize neuron reconstructions available in the NeuroMorpho database (www.neuromorpho.org) to assess the validity of the model we proposed by comparing morphological properties of the neurons to predictions based on diffusion MR simulations using the reconstructed neuron models. Initially, the method for directly determining neurite orientation distributions is shown to not depend on the line length used to quantify cylindrical elements. Further variability in neuron morphology is characterized relative to neuron type, species, and laboratory of origin. Subsequently, diffusion MR signals are simulated based on human neocortical neuron reconstructions. This reveals a bias in which diffusion MR data predict neuron orientation distributions to have artificially low anisotropy. This bias is shown to arise from shortcomings (already at relatively low diffusion weighting) in the Gaussian approximation of diffusion, in the presence of restrictive barriers, and data analysis methods involving higher moments of the cumulant expansion are shown to be capable of reducing the magnitude of the observed bias.

Digital reconstructions of neuronal morphology: three decades of research trends

The importance of neuronal morphology has been recognized from the early days of neuroscience. Elucidating the functional roles of axonal and dendritic arbors in synaptic integration, signal transmission, network connectivity, and circuit dynamics requires quantitative analyses of digital three-dimensional reconstructions. We extensively searched the scientific literature for all original reports describing reconstructions of neuronal morphology since the advent of this technique three decades ago. From almost 50,000 titles, 30,000 abstracts, and more than 10,000 full-text articles, we identified 902 publications describing ∼44,000 digital reconstructions. Reviewing the growth of this field exposed general research trends on specific animal species, brain regions, neuron types, and experimental approaches. The entire bibliography, annotated with relevant metadata and (wherever available) direct links to the underlying digital data, is accessible at NeuroMorpho.Org.