Nitrate (NO3-) uptake and distribution are critical to plant life. Although the upstream regulation of nitrate uptake and downstream responses to nitrate in a variety of cells have been well-studied, it is still not possible to directly visualize the spatial and temporal distribution of nitrate with high resolution at the cellular level. Here, we report a nuclear-localized, genetically encoded biosensor, nlsNitraMeter3.0, for the quantitative visualization of nitrate distribution in Arabidopsis thaliana. The biosensor tracked the spatiotemporal distribution of nitrate along the primary root axis and disruptions by genetic mutation of transport (low nitrate uptake) and assimilation (high nitrate accumulation). The developed biosensor effectively monitors nitrate concentrations at cellular level in real time and spatiotemporal changes during the plant life cycle.

Advances in microscopy hold great promise for allowing quantitative and precise measurement of morphological and molecular phenomena at the single-cell level in bacteria; however, the potential of this approach is ultimately limited by the availability of methods to faithfully segment cells independent of their morphological or optical characteristics. Here, we present Omnipose, a deep neural network image-segmentation algorithm. Unique network outputs such as the gradient of the distance field allow Omnipose to accurately segment cells on which current algorithms, including its predecessor, Cellpose, produce errors. We show that Omnipose achieves unprecedented segmentation performance on mixed bacterial cultures, antibiotic-treated cells and cells of elongated or branched morphology. Furthermore, the benefits of Omnipose extend to non-bacterial subjects, varied imaging modalities and three-dimensional objects. Finally, we demonstrate the utility of Omnipose in the characterization of extreme morphological phenotypes that arise during interbacterial antagonism. Our results distinguish Omnipose as a powerful tool for characterizing diverse and arbitrarily shaped cell types from imaging data.

RNA-guided systems, such as CRISPR-Cas, combine programmable substrate recognition with enzymatic function, a combination that has been used advantageously to develop powerful molecular technologies. Structural studies of these systems have illuminated how the RNA and protein jointly recognize and cleave their substrates, guiding rational engineering for further technology development. Recent work identified a new class of RNA-guided systems, termed OMEGA, which include IscB, the likely ancestor of Cas9, and the nickase IsrB, a homologue of IscB lacking the HNH nuclease domain. IsrB consists of only around 350 amino acids, but its small size is counterbalanced by a relatively large RNA guide (roughly 300-nt ωRNA). Here, we report the cryogenic-electron microscopy structure of Desulfovirgula thermocuniculi IsrB (DtIsrB) in complex with its cognate ωRNA and a target DNA. We find the overall structure of the IsrB protein shares a common scaffold with Cas9. In contrast to Cas9, however, which uses a recognition (REC) lobe to facilitate target selection, IsrB relies on its ωRNA, part of which forms an intricate ternary structure positioned analogously to REC. Structural analyses of IsrB and its ωRNA as well as comparisons to other RNA-guided systems highlight the functional interplay between protein and RNA, advancing our understanding of the biology and evolution of these diverse systems.

Brains must represent the outside world so that animals survive and thrive. In early sensory systems, neural populations have diverse receptive fields structured to detect important features in inputs, yet significant variability has been ignored in classical models of sensory neurons. We model neuronal receptive fields as random, variable samples from parameterized distributions and demonstrate this model in two sensory modalities using data from insect mechanosensors and mammalian primary visual cortex. Our approach leads to a significant theoretical connection between the foundational concepts of receptive fields and random features, a leading theory for understanding artificial neural networks. The modeled neurons perform a randomized wavelet transform on inputs, which removes high frequency noise and boosts the signal. Further, these random feature neurons enable learning from fewer training samples and with smaller networks in artificial tasks. This structured random model of receptive fields provides a unifying, mathematically tractable framework to understand sensory encodings across both spatial and temporal domains.

Cell-surface proteins (CSPs) mediate intercellular communication throughout the lives of multicellular organisms. However, there are no generalizable methods for quantitative CSP profiling in specific cell types in vertebrate tissues. Here, we present in situ cell-surface proteome extraction by extracellular labeling (iPEEL), a proximity labeling method in mice that enables spatiotemporally precise labeling of cell-surface proteomes in a cell-type-specific environment in native tissues for discovery proteomics. Applying iPEEL to developing and mature cerebellar Purkinje cells revealed differential enrichment in CSPs with post-translational protein processing and synaptic functions in the developing and mature cell-surface proteomes, respectively. A proteome-instructed in vivo loss-of-function screen identified a critical, multifaceted role for Armh4 in Purkinje cell dendrite morphogenesis. Armh4 overexpression also disrupts dendrite morphogenesis; this effect requires its conserved cytoplasmic domain and is augmented by disrupting its endocytosis. Our results highlight the utility of CSP profiling in native mammalian tissues for identifying regulators of cell-surface signaling.

Sensory areas are spontaneously active in the absence of sensory stimuli. This spontaneous activity has long been studied; however, its functional role remains largely unknown. Recent advances in technology, allowing large-scale neural recordings in the awake and behaving animal, have transformed our understanding of spontaneous activity. Studies using these recordings have discovered high-dimensional spontaneous activity patterns, correlation between spontaneous activity and behavior, and dissimilarity between spontaneous and sensory-driven activity patterns. These findings are supported by evidence from developing animals, where a transition toward these characteristics is observed as the circuit matures, as well as by evidence from mature animals across species. These newly revealed characteristics call for the formulation of a new role for spontaneous activity in neural sensory computation.

The neurophysiology of cells and tissues are monitored electrophysiologically and optically in diverse experiments and species, ranging from flies to humans. Understanding the brain requires integration of data across this diversity, and thus these data must be findable, accessible, interoperable, and reusable (FAIR). This requires a standard language for data and metadata that can coevolve with neuroscience. We describe design and implementation principles for a language for neurophysiology data. Our open-source software (Neurodata Without Borders, NWB) defines and modularizes the interdependent, yet separable, components of a data language. We demonstrate NWB's impact through unified description of neurophysiology data across diverse modalities and species. NWB exists in an ecosystem, which includes data management, analysis, visualization, and archive tools. Thus, the NWB data language enables reproduction, interchange, and reuse of diverse neurophysiology data. More broadly, the design principles of NWB are generally applicable to enhance discovery across biology through data FAIRness.

Embryonic stem (ES) cells can undergo many aspects of mammalian embryogenesis in vitro, but their developmental potential is substantially extended by interactions with extraembryonic stem cells, including trophoblast stem (TS) cells, extraembryonic endoderm stem (XEN) cells and inducible XEN (iXEN) cells. Here we assembled stem cell-derived embryos in vitro from mouse ES cells, TS cells and iXEN cells and showed that they recapitulate the development of whole natural mouse embryo in utero up to day 8.5 post-fertilization. Our embryo model displays headfolds with defined forebrain and midbrain regions and develops a beating heart-like structure, a trunk comprising a neural tube and somites, a tail bud containing neuromesodermal progenitors, a gut tube, and primordial germ cells. This complete embryo model develops within an extraembryonic yolk sac that initiates blood island development. Notably, we demonstrate that the neurulating embryo model assembled from Pax6-knockout ES cells aggregated with wild-type TS cells and iXEN cells recapitulates the ventral domain expansion of the neural tube that occurs in natural, ubiquitous Pax6-knockout embryos. Thus, these complete embryoids are a powerful in vitro model for dissecting the roles of diverse cell lineages and genes in development. Our results demonstrate the self-organization ability of ES cells and two types of extraembryonic stem cells to reconstitute mammalian development through and beyond gastrulation to neurulation and early organogenesis.

Summary Energy homeostasis requires precise measurement of the quantity and quality of ingested food. The vagus nerve innervates the gut and can detect diverse interoceptive cues, but the identity of the key sensory neurons and corresponding signals that regulate food intake remains unknown. Here, we use an approach for target-specific, single-cell RNA sequencing to generate a map of the vagal cell types that innervate the gastrointestinal tract. We show that unique molecular markers identify vagal neurons with distinct innervation patterns, sensory endings, and function. Surprisingly, we find that food intake is most sensitive to stimulation of mechanoreceptors in the intestine, whereas nutrient-activated mucosal afferents have no effect. Peripheral manipulations combined with central recordings reveal that intestinal mechanoreceptors, but not other cell types, potently and durably inhibit hunger-promoting AgRP neurons in the hypothalamus. These findings identify a key role for intestinal mechanoreceptors in the regulation of feeding.

The Meissner corpuscle, a mechanosensory end organ, was discovered more than 165 years ago and has since been found in the glabrous skin of all mammals, including that on human fingertips. Although prominently featured in textbooks, the function of the Meissner corpuscle is unknown. Neubarth et al. generated adult mice without Meissner corpuscles and used them to show that these corpuscles alone mediate behavioral responses to, and perception of, gentle forces (see the Perspective by Marshall and Patapoutian). Each Meissner corpuscle is innervated by two molecularly distinct, yet physiologically similar, mechanosensory neurons. These two neuronal subtypes are developmentally interdependent and their endings are intertwined within the corpuscle. Both Meissner mechanosensory neuron subtypes are homotypically tiled, ensuring uniform and complete coverage of the skin, yet their receptive fields are overlapping and offset with respect to each other. Science, this issue p. eabb2751; see also p. 1311 Light touch perception and fine sensorimotor control arise from spatially overlapping mechanoreceptors of the Meissner corpuscle. Meissner corpuscles are mechanosensory end organs that densely occupy mammalian glabrous skin. We generated mice that selectively lacked Meissner corpuscles and found them to be deficient in both perceiving the gentlest detectable forces acting on glabrous skin and fine sensorimotor control. We found that Meissner corpuscles are innervated by two mechanoreceptor subtypes that exhibit distinct responses to tactile stimuli. The anatomical receptive fields of these two mechanoreceptor subtypes homotypically tile glabrous skin in a manner that is offset with respect to one another. Electron microscopic analysis of the two Meissner afferents within the corpuscle supports a model in which the extent of lamellar cell wrappings of mechanoreceptor endings determines their force sensitivity thresholds and kinetic properties.