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The dorsal raphe nucleus (DRN) is an important source of neuromodulators and has been implicated in a wide variety of behavioral and neurological disorders. The DRN is subdivided into distinct anatomical subregions comprised of multiple cell types, and its complex cellular organization has impeded efforts to investigate the distinct circuit and behavioral functions of its subdomains. Here we used single-cell RNA sequencing, in situ hybridization, anatomical tracing, and spatial correlation analysis to map the transcriptional and spatial profiles of cells from the mouse DRN. Our analysis of 39,411 single-cell transcriptomes revealed at least 18 distinct neuron subtypes and 5 serotonergic neuron subtypes with distinct molecular and anatomical properties, including a serotonergic neuron subtype that preferentially innervates the basal ganglia. Our study lays out the molecular organization of distinct serotonergic and non-serotonergic subsystems, and will facilitate the design of strategies for further dissection of the DRN and its diverse functions.

The bundle of stereocilia on inner ear hair cells responds to subnanometer deflections produced by sound or head movement. Stereocilia are interconnected by a variety of links and also carry an electron-dense surface coat. The coat may contribute to stereocilia adhesion or protect from stereocilia fusion, but its molecular identity remains unknown. From a database of hair-cell-enriched translated proteins, we identify Polycystic Kidney and Hepatic Disease 1-Like 1 (PKHD1L1), a large, mostly extracellular protein of 4249 amino acids with a single transmembrane domain. Using serial immunogold scanning electron microscopy, we show that PKHD1L1 is expressed at the tips of stereocilia, especially in the high-frequency regions of the cochlea. PKHD1L1-deficient mice lack the surface coat at the upper but not lower regions of stereocilia, and they develop progressive hearing loss. We conclude that PKHD1L1 is a component of the surface coat and is required for normal hearing in mice. There is little known about the function or molecular identity of the electron-dense stereocilia coat, which is transiently present at the surface of stereocilia. In this study authors screened a database of hair-cell-enriched translated proteins to identify the expression of Polycystic Kidney and Hepatic Disease 1-Like 1 (PKHD1L1), a large, mostly extracellular protein, and show that it forms the coat at the tips of stereocilia and is required for normal hearing in mice

Nrf2, a transcription factor that regulates the response to oxidative stress, has been shown to rescue cone photoreceptors and slow vision loss in mouse models of retinal degeneration (rd). The retinal pigment epithelium (RPE) is damaged in these models, but whether it also could be rescued by Nrf2 has not been previously examined. We used an adeno-associated virus (AAV) with an RPE-specific (Best1) promoter to overexpress Nrf2 in the RPE of rd mice. Control rd mice showed disruption of the regular array of the RPE, as well as loss of RPE cells. Cones were lost in circumscribed regions within the cone photoreceptor layer. Overexpression of Nrf2 specifically in the RPE was sufficient to rescue the RPE, as well as the disruptions in the cone photoreceptor layer. Electron microscopy showed compromised apical microvilli in control rd mice but showed preserved microvilli in Best1-Nrf2-treated mice. The rd mice treated with Best1-Nrf2 had slightly better visual acuity. Transcriptome profiling showed that Nrf2 upregulates multiple oxidative defense pathways, reversing declines seen in the glutathione pathway in control rd mice. In summary, Nrf2 overexpression in the RPE preserves RPE morphology and survival in rd mice, and it is a potential therapeutic for diseases involving RPE degeneration, including age-related macular degeneration (AMD).

Upcoming technologies enable routine collection of highly multiplexed (20–60 channel), subcellular resolution images of mammalian tissues for research and diagnosis. Extracting single cell data from such images requires accurate image segmentation, a challenging problem commonly tackled with deep learning. In this paper, we report two findings that substantially improve image segmentation of tissues using a range of machine learning architectures. First, we unexpectedly find that the inclusion of intentionally defocused and saturated images in training data substantially improves subsequent image segmentation. Such real augmentation outperforms computational augmentation (Gaussian blurring). In addition, we find that it is practical to image the nuclear envelope in multiple tissues using an antibody cocktail thereby better identifying nuclear outlines and improving segmentation. The two approaches cumulatively and substantially improve segmentation on a wide range of tissue types. We speculate that the use of real augmentations will have applications in image processing outside of microscopy. Presenting UnMICST, strategies for robust single-cell segmentation in challenging human tissues.

The void spot assay has gained popularity as a way of assessing functional bladder voiding parameters in mice, but analyzing the size and distribution of urine spot patterns on filter paper with software remains problematic due to inter‐laboratory differences in image contrast and resolution quality and non‐void artifacts. We have developed a machine learning algorithm based on Region‐based Convolutional Neural Networks (Mask‐RCNN) that was trained in object recognition to detect and quantitate urine spots across a broad range of sizes—ML‐UrineQuant. The model proved extremely accurate at identifying urine spots in a wide variety of illumination and contrast settings. The overwhelming advantage it offers over current algorithms will be to allow individual labs to fine‐tune the model on their specific images regardless of the image characteristics. This should be a valuable tool for anyone performing lower urinary tract research using mouse models.

Serial electron microscopy techniques have proven to be a powerful tool in biology. Unfortunately, the data sets they generate lack robust and accurate automated segmentation algorithms. In this data descriptor publication, we introduce a serial focused ion beam scanning electron microscopy (FIB-SEM) dataset consisting of six outer hair cell (OHC) stereocilia bundles, and the supranuclear part of the hair cell bodies. Also presented are the manual segmentations of stereocilia bundles and the gold bead labeling of PKHD1L1, a coat protein of hair cell stereocilia important for hearing in mice. This depository includes all original data and several intermediate steps of the manual analysis, as well as the MATLAB algorithm used to generate a three-dimensional distribution map of gold labels. They serve as a reference dataset, and they enable reproduction of our analysis, evaluation and improvement of current methods of protein localization, and training of algorithms for accurate automated segmentation. Measurement(s) outer hair cell • cochlear hair cell Technology Type(s) scanning electron micrograph Factor Type(s) anti-PKHD1L1 labeling distribution Sample Characteristic - Organism Mus musculus Machine-accessible metadata file describing the reported data: https://doi.org/10.6084/m9.figshare.12210158

Activity-dependent transcriptional responses shape cortical function. However, a comprehensive understanding of the diversity of these responses across the full range of cortical cell types, and how these changes contribute to neuronal plasticity and disease, is lacking. To investigate the breadth of transcriptional changes that occur across cell types in the mouse visual cortex after exposure to light, we applied high-throughput single-cell RNA sequencing. We identified significant and divergent transcriptional responses to stimulation in each of the 30 cell types characterized, thus revealing 611 stimulus-responsive genes. Excitatory pyramidal neurons exhibited inter- and intralaminar heterogeneity in the induction of stimulus-responsive genes. Non-neuronal cells showed clear transcriptional responses that may regulate experience-dependent changes in neurovascular coupling and myelination. Together, these results reveal the dynamic landscape of the stimulus-dependent transcriptional changes occurring across cell types in the visual cortex; these changes are probably critical for cortical function and may be sites of deregulation in developmental brain disorders.

The advent of endothermy, which is achieved through the continuous homeostatic regulation of body temperature and metabolism 1 , 2 , is a defining feature of mammalian and avian evolution. However, when challenged by food deprivation or harsh environmental conditions, many mammalian species initiate adaptive energy-conserving survival strategies—including torpor and hibernation—during which their body temperature decreases far below its homeostatic set-point 3 – 5 . How homeothermic mammals initiate and regulate these hypothermic states remains largely unknown. Here we show that entry into mouse torpor, a fasting-induced state with a greatly decreased metabolic rate and a body temperature as low as 20 °C 6 , is regulated by neurons in the medial and lateral preoptic area of the hypothalamus. We show that restimulation of neurons that were activated during a previous bout of torpor is sufficient to initiate the key features of torpor, even in mice that are not calorically restricted. Among these neurons we identify a population of glutamatergic Adcyap1 -positive cells, the activity of which accurately determines when mice naturally initiate and exit torpor, and the inhibition of which disrupts the natural process of torpor entry, maintenance and arousal. Taken together, our results reveal a specific neuronal population in the mouse hypothalamus that serves as a core regulator of torpor. This work forms a basis for the future exploration of mechanisms and circuitry that regulate extreme hypothermic and hypometabolic states, and enables genetic access to monitor, initiate, manipulate and study these ancient adaptations of homeotherm biology. A specific neuronal population in the medial and lateral preoptic area of the hypothalamus regulates entry into torpor in mice.

A complete larval zebrafish brain is examined and its myelinated axons reconstructed using serial-section electron microscopy, revealing remarkable symmetry and providing a valuable resource. Mapping the zebrafish brain Reconstructing neuronal circuits through serial-section electron microscopy (ssEM) requires a sub-nanoscale resolution that is more than 10 orders of magnitude smaller than whole vertebrate brains. This has limited connectomics efforts to elucidate restricted circuits. Florian Engert and colleagues report the ssEM reconstruction of a complete larval zebrafish brain, which reveals remarkable bilateral symmetry in the myelinated axon 'projectome'. The work further illustrates how such datasets can guide co-registering of structural and functional imaging data from a same specimen. High-resolution serial-section electron microscopy (ssEM) makes it possible to investigate the dense meshwork of axons, dendrites, and synapses that form neuronal circuits 1 . However, the imaging scale required to comprehensively reconstruct these structures is more than ten orders of magnitude smaller than the spatial extents occupied by networks of interconnected neurons 2 , some of which span nearly the entire brain. Difficulties in generating and handling data for large volumes at nanoscale resolution have thus restricted vertebrate studies to fragments of circuits. These efforts were recently transformed by advances in computing, sample handling, and imaging techniques 1 , but high-resolution examination of entire brains remains a challenge. Here, we present ssEM data for the complete brain of a larval zebrafish ( Danio rerio ) at 5.5 days post-fertilization. Our approach utilizes multiple rounds of targeted imaging at different scales to reduce acquisition time and data management requirements. The resulting dataset can be analysed to reconstruct neuronal processes, permitting us to survey all myelinated axons (the projectome). These reconstructions enable precise investigations of neuronal morphology, which reveal remarkable bilateral symmetry in myelinated reticulospinal and lateral line afferent axons. We further set the stage for whole-brain structure–function comparisons by co-registering functional reference atlases and in vivo two-photon fluorescence microscopy data from the same specimen. All obtained images and reconstructions are provided as an open-access resource.

Pathways localizing proteins to their sites of action are essential for eukaryotic cell organization and function. Although mechanisms of protein targeting to many organelles have been defined, how proteins, such as metabolic enzymes, target from the endoplasmic reticulum (ER) to cellular lipid droplets (LDs) is poorly understood. Here we identify two distinct pathways for ER-to-LD protein targeting: early targeting at LD formation sites during formation, and late targeting to mature LDs after their formation. Using systematic, unbiased approaches in Drosophila cells, we identified specific membrane-fusion machinery, including regulators, a tether and SNARE proteins, that are required for the late targeting pathway. Components of this fusion machinery localize to LD–ER interfaces and organize at ER exit sites. We identified multiple cargoes for early and late ER-to-LD targeting pathways. Our findings provide a model for how proteins target to LDs from the ER either during LD formation or by protein-catalysed formation of membrane bridges. Song et al. identify two protein-targeting pathways from the endoplasmic reticulum to (1) early lipid droplets (LDs) and (2) mature lipid droplets. They define key factors mediating the second, late pathway and its many cargoes.