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Connectomics is fundamental in propelling our understanding of the nervous system’s organization, unearthing cells and wiring diagrams reconstructed from volume electron microscopy (EM) datasets. Such reconstructions, on the one hand, have benefited from ever more precise automatic segmentation methods, which leverage sophisticated deep learning architectures and advanced machine learning algorithms. On the other hand, the field of neuroscience at large, and of image processing in particular, has manifested a need for user-friendly and open source tools which enable the community to carry out advanced analyses. In line with this second vein, here we propose mEMbrain, an interactive MATLAB-based software which wraps algorithms and functions that enable labeling and segmentation of electron microscopy datasets in a user-friendly user interface compatible with Linux and Windows. Through its integration as an API to the volume annotation and segmentation tool VAST, mEMbrain encompasses functions for ground truth generation, image preprocessing, training of deep neural networks, and on-the-fly predictions for proofreading and evaluation. The final goals of our tool are to expedite manual labeling efforts and to harness MATLAB users with an array of semi-automatic approaches for instance segmentation. We tested our tool on a variety of datasets that span different species at various scales, regions of the nervous system and developmental stages. To further expedite research in connectomics, we provide an EM resource of ground truth annotation from 4 different animals and 5 datasets, amounting to around 180 hours of expert annotations, yielding more than 1.2 GB of annotated EM images. In addition, we provide a set of 4 pre-trained networks for said datasets. All tools are available fromhttps://lichtman.rc.fas.harvard.edu/mEMbrain/. With our software, our hope is to provide a solution for lab-based neural reconstructions which does not require coding by the user, thus paving the way to affordable connectomics.

Specialized mechanosensory end organs within mammalian skin—hair follicle-associated lanceolate complexes, Meissner corpuscles, and Pacinian corpuscles—enable our perception of light, dynamic touch1. In each of these end organs, fast-conducting mechanically sensitive neurons, called Aβ low-threshold mechanoreceptors (Aβ LTMRs), associate with resident glial cells, known as terminal Schwann cells (TSCs) or lamellar cells, to form complex axon ending structures. Lanceolate-forming and corpuscle-innervating Aβ LTMRs share a low threshold for mechanical activation, a rapidly adapting (RA) response to force indentation, and high sensitivity to dynamic stimuli1–6. How mechanical stimuli lead to activation of the requisite mechanotransduction channel Piezo27–15and Aβ RA-LTMR excitation across the morphologically dissimilar mechanosensory end organ structures is not understood. Here, we report the precise subcellular distribution of Piezo2 and high-resolution, isotropic 3D reconstructions of all three end organs formed by Aβ RA-LTMRs determined by large volume enhanced Focused Ion Beam Scanning Electron Microscopy (FIB-SEM) imaging. We found that within each end organ, Piezo2 is enriched along the sensory axon membrane and is minimally or not expressed in TSCs and lamellar cells. We also observed a large number of small cytoplasmic protrusions enriched along the Aβ RA-LTMR axon terminals associated with hair follicles, Meissner corpuscles, and Pacinian corpuscles. These axon protrusions reside within close proximity to axonal Piezo2, occasionally contain the channel, and often form adherens junctions with nearby non-neuronal cells. Our findings support a unified model for Aβ RA-LTMR activation in which axon protrusions anchor Aβ RA-LTMR axon terminals to specialized end organ cells, enabling mechanical stimuli to stretch the axon in hundreds to thousands of sites across an individual end organ and leading to activation of proximal Piezo2 channels and excitation of the neuron.

SummaryNeural activity is increasingly recognized as a critical regulator of cancer growth. In the brain, neuronal activity robustly influences glioma growth both through paracrine mechanisms and through electrochemical integration of malignant cells into neural circuitry via neuron-to-glioma synapses, while perisynaptic neurotransmitter signaling drives breast cancer brain metastasis growth. Outside of the CNS, innervation of tumors such as prostate, breast, pancreatic and gastrointestinal cancers by peripheral nerves similarly regulates cancer progression. However, the extent to which the nervous system regulates lung cancer progression, either in the lung or when metastatic to brain, is largely unexplored. Small cell lung cancer (SCLC) is a lethal high-grade neuroendocrine tumor that exhibits a strong propensity to metastasize to the brain. Here we demonstrate that, similar to glioma, metastatic SCLC cells in the brain co-opt neuronal activity-regulated mechanisms to stimulate growth and progression. Optogenetic stimulation of cortical neuronal activity drives proliferation and invasion of SCLC brain metastases. In the brain, SCLC cells exhibit electrical currents and consequent calcium transients in response to neuronal activity, and direct SCLC cell membrane depolarization is sufficient to promote the growth of SCLC tumors. In the lung, vagus nerve transection markedly inhibits primary lung tumor formation, progression and metastasis, highlighting a critical role for innervation in overall SCLC initiation and progression. Taken together, these studies illustrate that neuronal activity plays a crucial role in dictating SCLC pathogenesis in both primary and metastatic sites.

In mammals, the connections between motor neurons and muscle fibers profoundly reorganize in the early postnatal period. To better understand this synaptic rewiring we traced out all the connectivity in muscles at successive ages in the mouse using serial section scanning electron microscopy in a muscle at birth and Brainbow-based and XFP-based fluorescent reconstructions in neonatal and older muscles respectively. Our data indicate that axons prune about 85% of their branches in the first two weeks of postnatal life, and that while much of this pruning leaves neuromuscular junctions with only one remaining axon (a ∼8-fold reduction), it also causes a ∼6-fold reduction in the number of muscle fibers that possess more than one neuromuscular junction. Unexpectedly, the simplification of the wiring diagram was not haphazard but rather was constrained by the tendency for neurons to maintain co-innervation the longest with other neurons based on their proximity in an abstract rank order. This synaptic ordering preference was even significant at birth when connectivity was the most overlapping but became more striking as development proceeded and was even obvious in the few adult muscle fibers that retained more than one axon at different neuromuscular junctions. Analysis of properties of muscle fibers sharing axons at developing ages and changes in the physical distance between neuromuscular junctions that were maintained in young versus older muscles suggests that the rank order of motor neurons is based on their relative similarity in activity patterns. This same ranking governs both the close-proximity synaptic competitions within neuromuscular junctions and the long-distance competitions that remove or maintain synapses millimeters apart meaning that all neuromuscular rewiring is based on the same global activity ordering rule. We think it is likely that this ranking is related to the ultimate recruitment order of motor axon activity as first described by (Henneman, 1957). Thus the emerging structure of neuromuscular circuitry is a product of its function: initial nearly all-to-all connectivity gives rise to a well-organized system of axons, allowing for the orderly recruitment of neurons during a smoothly graded behavior.