Fitting Splines to Axonal Arbors Quantifies Relationship Between Branch Order and Geometry

Neuromorphology is crucial to identifying neuronal subtypes and understanding learning. It is also implicated in neurological disease. However, standard morphological analysis focuses on macroscopic features such as branching frequency and connectivity between regions, and often neglects the internal geometry of neurons. In this work, we treat neuron trace points as a sampling of differentiable curves and fit them with a set of branching B-splines. We designed our representation with the Frenet-Serret formulas from differential geometry in mind. The Frenet-Serret formulas completely characterize smooth curves, and involve two parameters, curvature and torsion. Our representation makes it possible to compute these parameters from neuron traces in closed form. These parameters are defined continuously along the curve, in contrast to other parameters like tortuosity which depend on start and end points. We applied our method to a dataset of cortical projection neurons traced in two mouse brains, and found that the parameters are distributed differently between primary, collateral, and terminal axon branches, thus quantifying geometric differences between different components of an axonal arbor. The results agreed in both brains, further validating our representation. The code used in this work can be readily applied to neuron traces in SWC format and is available in our open-source Python package brainlit: http://brainlit.neurodata.io/.

Neonatal 6-OHDA lesion of the SNc induces striatal compensatory sprouting from surviving SNc dopaminergic neurons without VTA contribution

Dopamine (DA) neurons of the substantia nigra pars compacta (SNc) are uniquely vulnerable to neurodegeneration in Parkinson’s disease (PD). We hypothesize that their large axonal arbor is a key factor underlying their vulnerability, due to increased bioenergetic, proteostatic and oxidative stress. In keeping with this model, other DAergic populations with smaller axonal arbors are mostly spared during the course of PD and are more resistant to experimental lesions in animal models. Aiming to improve mouse PD models, we examined if neonatal partial SNc lesions could lead to adult mice with fewer SNc DA neurons that are endowed with larger axonal arbors because of compensatory mechanisms. We injected 6-hydroxydopamine (6-OHDA) unilaterally in the SNc at an early postnatal stage at a dose selected to induce loss of approximately 50% of SNc DA neurons. We find that at 10- and 90-days after the lesion, the axons of SNc DA neurons show massive compensatory sprouting, as revealed by the proportionally smaller decrease in tyrosine hydroxylase (TH) in the striatum compared to the loss of SNc DA neuron cell bodies. The extent and origin of this axonal sprouting was further investigated by AAV-mediated expression of eYFP in SNc or ventral tegmental area (VTA) DA neurons of adult mice. Our results reveal that SNc DA neurons have the capacity to substantially increase their axonal arbor size and suggest that mice designed to have reduced numbers of SNc DA neurons could potentially be used to develop better mouse models of PD, with elevated neuronal vulnerability.Graphical abstract textWe describe a technique to induce the loss of approximately 50% of SNc DA neurons in neonate mice using unilateral intranigral 6-OHDA (left panel).Compensatory axonal sprouting was observed in the striatum as early as 10 days following the lesion (at P15), with effects lasting until adulthood (P90).Conditional AAV-mediated expression of eYFP (green) reveals SNc DA neurons, projecting to the dorsal striatum (middle panel), and not VTA DA neurons, projecting to the ventral striatum (right panel), as the main source of compensatory axonal sprouting.Graphical abstract

Intermitochondrial signaling regulates the uniform distribution of stationary mitochondria in axons

ABSTRACTIn the central nervous system, many neurons develop axonal arbors that are crucial for information processing. Previous studies have demonstrated that premature axons contain motile and stationary mitochondria, and their balance is important for axonal arborization. However, the mechanisms by which neurons determine the positions of stationary mitochondria as well as their turnover remain to be elucidated. In this study, we investigated the regulation of spatiotemporal group dynamics of stationary mitochondria. We observed that the distribution of stationary mitochondrial spots along the unmyelinated and nonsynaptic axons is not random but rather relatively uniform both in vitro and in vivo. Intriguingly, whereas the positions of each mitochondrial spot changed over time, the overall distribution remained uniform. In addition, local inactivation of mitochondria inhibited the translocation of mitochondrial spots in adjacent axonal regions, suggesting that functional mitochondria enhance the motility of neighboring mitochondria. Furthermore, we showed that the ATP concentration was relatively high around mitochondria, and treating axons with phosphocreatine, which supplies ATP, reduced the immobile mitochondria induced by local mitochondrial inhibition. These observations indicate that intermitochondrial interactions, mediated by ATP signaling, control the uniform distribution of axonal mitochondria. The present study reveals a novel cellular system that collectively regulates stationary mitochondria in axons.

Bitbow: a digital format of Brainbow enables highly efficient neuronal lineage tracing and morphology reconstruction in single brains

Identifying the cellular origins and mapping the dendritic and axonal arbors of neurons have been century old quests to understand the heterogeneity among these brain cells. Classical chemical and genetic methods take advantage of light microscopy and sparse labeling to unambiguously, albeit inefficiently, trace a few neuronal lineages or reconstruct their morphologies in each sampled brain. To improve the analysis throughput, we designed Bitbow, a digital format of Brainbow which exponentially expands the color palette to provide tens of thousands of spectrally resolved unique labels. We generated transgenic Bitbow Drosophila lines, established statistical tools, and streamlined sample preparation, image processing and data analysis pipelines to allow conveniently mapping neural lineages, studying neuronal morphology and revealing neural network patterns with an unprecedented speed, scale and resolution.

The forebrain synaptic transcriptome is organized by clocks but its proteome is driven by sleep

Neurons have adapted mechanisms to traffic RNA and protein into distant dendritic and axonal arbors. Taking a biochemical approach, we reveal that forebrain synaptic transcript accumulation shows overwhelmingly daily rhythms, with two-thirds of synaptic transcripts showing time-of-day–dependent abundance independent of oscillations in the soma. These transcripts formed two sharp temporal and functional clusters, with transcripts preceding dawn related to metabolism and translation and those anticipating dusk related to synaptic transmission. Characterization of the synaptic proteome around the clock demonstrates the functional relevance of temporal gating for synaptic processes and energy homeostasis. Unexpectedly, sleep deprivation completely abolished proteome but not transcript oscillations. Altogether, the emerging picture is one of a circadian anticipation of messenger RNA needs in the synapse followed by translation as demanded by sleep-wake cycles.