Understanding circuit organization depends on identification of cell types. Recent advances in transcriptional profiling methods have enabled classification of cell types by their gene expression. While exceptionally powerful and high throughput, the ground-truth validation of these methods is difficult: If cell type is unknown, how does one assess whether a given analysis accurately captures neuronal identity? To shed light on the capabilities and limitations of solely using transcriptional profiling for cell-type classification, we performed 2 forms of transcriptional profiling—RNA-seq and quantitative RT-PCR, in single, unambiguously identified neurons from 2 small crustacean neuronal networks: The stomatogastric and cardiac ganglia. We then combined our knowledge of cell type with unbiased clustering analyses and supervised machine learning to determine how accurately functionally defined neuron types can be classified by expression profile alone. The results demonstrate that expression profile is able to capture neuronal identity most accurately when combined with multimodal information that allows for post hoc grouping, so analysis can proceed from a supervised perspective. Solely unsupervised clustering can lead to misidentification and an inability to distinguish between 2 or more cell types. Therefore, this study supports the general utility of cell identification by transcriptional profiling, but adds a caution: It is difficult or impossible to know under what conditions transcriptional profiling alone is capable of assigning cell identity. Only by combining multiple modalities of information such as physiology, morphology, or innervation target can neuronal identity be unambiguously determined.

Understanding circuit organization depends on identification of cell types. Recent advances in transcriptional profiling methods have enabled classification of cell types by their gene expression. While exceptionally powerful and high throughput, the ground-truth validation of these methods is difficult: if cell type is unknown, how does one assess whether a given analysis accurately captures neuronal identity? To shed light on the capabilities and limitations of solely using transcriptional profiling for cell type classification, we performed two forms of transcriptional profiling – RNA-seq and quantitative RT-PCR, in single, unambiguously identified neurons from two small crustacean networks: the stomatogastric and cardiac ganglia. We then combined our knowledge of cell type with unbiased clustering analyses and supervised machine learning to determine how accurately functionally-defined neuron types can be classified by expression profile alone. Our results demonstrate that expression profile is able to capture neuronal identity most accurately when combined with multimodal information that allows for post-hoc grouping so analysis can proceed from a supervised perspective. Solely unsupervised clustering can lead to misidentification and an inability to distinguish between two or more cell types. Therefore, our study supports the general utility of cell identification by transcriptional profiling, but adds a caution: it is difficult or impossible to know under what conditions transcriptional profiling alone is capable of assigning cell identity. Only by combining multiple modalities of information such as physiology, morphology or innervation target can neuronal identity be unambiguously determined.SIGNIFICANCE STATEMENT Single cell transcriptional profiling has become a widespread tool in cell identification, particularly in the nervous system, based on the notion that genomic information determines cell identity. However, many cell type classification studies are unconstrained by other cellular attributes (e.g., morphology, physiology). Here, we systematically test how accurately transcriptional profiling can assign cell identity to well-studied anatomically- and functionally-identified neurons in two small neuronal networks. While these neurons clearly possess distinct patterns of gene expression across cell types, their expression profiles are not sufficient to unambiguously confirm their identity. We suggest that true cell identity can only be determined by combining gene expression data with other cellular attributes such as innervation pattern, morphology, or physiology.

Interoceptors, sensory neurons that monitor internal organs and states, are essential for physiological homeostasis and generating internal perceptions. Here we describe a comprehensive transcriptomic atlas of interoceptors of the mouse lung, defining 10 molecular subtypes that differ in developmental origin, myelination, receptive fields, terminal morphologies, and cell contacts. Each subtype expresses a unique but overlapping combination of sensory receptors that detect diverse physiological and pathological stimuli, and each can signal to distinct sets of lung cells including immune cells, forming a local neuroimmune interaction network. Functional interrogation of two mechanosensory subtypes reveals exquisitely-specific homeostatic roles in breathing, one regulating inspiratory time and the other inspiratory flow. The results suggest that lung interoceptors encode diverse and dynamic sensory information rivaling that of canonical exteroceptors, and this information is used to drive myriad local cellular interactions and enable precision control of breathing, while providing only vague perceptions of organ states.Competing Interest StatementThe authors have declared no competing interest.

The sympathetic and parasympathetic nervous systems regulate the activities of internal organs1, but the molecular and functional diversity of their constituent neurons and circuits remains largely unknown. Here we use retrograde neuronal tracing, single-cell RNA sequencing, optogenetics and physiological experiments to dissect the cardiac parasympathetic control circuit in mice. We show that cardiac-innervating neurons in the brainstem nucleus ambiguus (Amb) are comprised of two molecularly, anatomically and functionally distinct subtypes. The first, which we call ambiguus cardiovascular (ACV) neurons (approximately 35 neurons per Amb), define the classical cardiac parasympathetic circuit. They selectively innervate a subset of cardiac parasympathetic ganglion neurons and mediate the baroreceptor reflex, slowing heart rate and atrioventricular node conduction in response to increased blood pressure. The other, ambiguus cardiopulmonary (ACP) neurons (approximately 15 neurons per Amb) innervate cardiac ganglion neurons intermingled with and functionally indistinguishable from those innervated by ACV neurons. ACP neurons also innervate most or all lung parasympathetic ganglion neurons—clonal labelling shows that individual ACP neurons innervate both organs. ACP neurons mediate the dive reflex, the simultaneous bradycardia and bronchoconstriction that follows water immersion. Thus, parasympathetic control of the heart is organized into two parallel circuits, one that selectively controls cardiac function (ACV circuit) and another that coordinates cardiac and pulmonary function (ACP circuit). This new understanding of cardiac control has implications for treating cardiac and pulmonary diseases and for elucidating the control and coordination circuits of other organs.

In mammals, subplate neurons (SPNs) are among the first generated cortical neurons. While most SPNs exist only transiently during development, a number of SPNs persist among adult Layer 6b (L6b). During development, SPNs receive thalamic and intra-cortical input, and primarily project to Layer 4 (L4). SPNs are critical for the anatomical and functional development of thalamocortical connections and also pioneer corticothalamic projections. Since SPNs are heterogeneous, SPN subpopulations might serve different roles. Here, we investigate the connectivity of one subpopulation, complexin-3 (Cplx3)-positive SPNs (Cplx3-SPNs), in mouse whisker somatosensory (barrel) cortex (S1). We find that many Cplx3-SPNs survive into adulthood and become a subpopulation of L6b. Cplx3-SPNs axons project to thalamorecipient layers, that is, L4, 5a, and 1. The L4 projections are biased towards the septal regions between barrels in the second postnatal week. Thus, S1 Cplx3-SPN targets co-localize with the eventual projections of the medial posterior thalamic nucleus (POm). In addition to their cortical targets, Cplx3-SPNs also extend long-range axons to several thalamic nuclei, including POm. Thus, Cplx3-SPN/L6b neurons are associated with paralemniscal pathways and can potentially directly link thalamocortical and corticothalamic circuits. This suggests an additional key role for SPNs in the establishment and maintenance of thalamocortical processing.

A miniature, handheld mass spectrometer, based on the rectilinear ion trap mass analyzer, has been applied to air monitoring for traces of toxic compounds. The instrument is battery-operated, hand-portable, and rugged. We anticipate its use in public safety, industrial hygiene, and environmental monitoring. Gaseous samples of nine toxic industrial compounds, phosgene, ethylene oxide, sulfur dioxide, acrylonitrile, cyanogen chloride, hydrogen cyanide, acrolein, formaldehyde, and ethyl parathion, were tested. A sorption trap inlet was constructed to serve as the interface between atmosphere and the vacuum chamber of the mass spectrometer. After selective collection of analytes on the sorbent bed, the sorbent tube was evacuated and then heated to desorb analyte into the instrument. Sampling, detection, identification, and quantitation of all compounds were readily achieved in times of less than 2 min, with detection limits ranging from 800 parts per trillion to 3 parts per million depending on the analyte. For all but one analyte, detection limits were well below (3.5-130 times below) permissible exposure limits. A linear dynamic range of 1-2 orders of magnitude was obtained over the concentration ranges studied (sub-ppbv to ppmv) for all analytes.

This protocol describes how to apply appropriate pharmacological controls to induce mitochondrial fusion or fission in studies of mitochondria morphology for four different mammalian cell types, HepG2 human liver hepatocellular carcinoma cells, MCF7 human breast adenocarcinoma cells, HEK293 human embryonic kidney cells, and collagen sandwich culture of primary rat hepatocytes. The protocol provides methods of treating cells with these pharmacological controls, staining mitochondria with commercially available MitoTracker Green and TMRE dyes, and imaging the mitochondrial morphology in live cells using a confocal fluorescent microscope. It also describes the cell culture methods needed for this protocol. © 2018 by John Wiley & Sons, Inc.

We identified moody in a genetic screen for Drosophila mutants with altered cocaine sensitivity. Hypomorphic mutations in moody cause an increased sensitivity to cocaine and nicotine exposure. In contrast, sensitivity to the acute intoxicating effects of ethanol is reduced. The moody locus encodes two novel GPCRs, Moody-alpha and Moody-beta. While identical in their membrane-spanning domains, the two Moody proteins differ in their long carboxy-terminal domains, which are generated by use of alternative reading frames. Both Moody forms are required for normal cocaine sensitivity, suggesting that they carry out distinct but complementary functions. Moody-alpha and Moody-beta are coexpressed in surface glia that surround the nervous system, where they are actively required to maintain the integrity of the blood-brain barrier in the adult fly. We propose that a Moody-mediated signaling pathway functions in glia to regulate nervous system insulation and drug-related behaviors.

Insects, like most animals, tend to steer away from imminent threats [1-7]. Drosophila melanogaster, for example, generally initiate an escape take-off in response to a looming visual stimulus, mimicking a potential predator [8]. The escape response to a visual threat is, however, flexible [9-12] and can alternatively consist of walking backward away from the perceived threat [11], which may be a more effective response to ambush predators such as nymphal praying mantids [7]. Flexibility in escape behavior may also add an element of unpredictability that makes it difficult for predators to anticipate or learn the prey's likely response [3-6]. Whereas the fly's escape jump has been well studied [8, 9, 13-18], the neuronal underpinnings of evasive walking remain largely unexplored. We previously reported the identification of a cluster of descending neurons-the moonwalker descending neurons (MDNs)-the activity of which is necessary and sufficient to trigger backward walking [19], as well as a population of visual projection neurons-the lobula columnar 16 (LC16) cells-that respond to looming visual stimuli and elicit backward walking and turning [11]. Given the similarity of their activation phenotypes, we hypothesized that LC16 neurons induce backward walking via MDNs and that turning while walking backward might reflect asymmetric activation of the left and right MDNs. Here, we present data from functional imaging, behavioral epistasis, and unilateral activation experiments that support these hypotheses. We conclude that LC16 and MDNs are critical components of the neural circuit that transduces threatening visual stimuli into directional locomotor output.

The accelerating pace of technological advancements necessitates specialised expertise and cutting-edge instruments to maintain competitive research in life sciences. Core facilities - collaborative laboratories equipped with state-of-the-art tools and staffed by expert personnel - are vital resources that support diverse scientific endeavours. However, their adoption in lower-income communities has been comparatively stagnant due to both financial and cultural challenges. This paper explores the perils of not supporting core facilities on national research enterprises, underscoring the need for balanced investments in discovery science and crucial infrastructure support. We explore the implications from the perspectives of funders, university leaders and lab heads. We advocate for a paradigm shift to recognise these facilities as essential components of national research efforts. Core facilities are positioned not as optional but as strategic investments that can catalyse breakthroughs, particularly in environments with limited resources.