Coordinated motor behaviors depend on feedback communication between peripheral sensory systems and central circuits in the brain and spinal cord. Relay of muscle and tendon-derived sensory information to the CNS is facilitated by functionally and anatomically diverse groups of spinocerebellar tract neurons (SCTNs), but the molecular logic by which SCTN diversity and connectivity is achieved is poorly understood. We used single cell RNA sequencing and genetic manipulations to define the mechanisms governing the molecular profile and organization of SCTN subtypes. We found that SCTNs relaying proprioceptive sensory information from limb and axial muscles are generated through segmentally-restricted actions of specific Hox genes. Loss of Hox function disrupts SCTN subtype-specific transcriptional programs, leading to defects in the connections between proprioceptive sensory neurons, SCTNs, and the cerebellum. These results indicate that Hox-dependent genetic programs play essential roles in the assembly of the neural circuits required for proprioception.

Focal adhesions (FAs) link the extracellular matrix to the actin cytoskeleton to mediate cell adhesion, migration, mechanosensing and signalling. FAs have conserved nanoscale protein organization, suggesting that the position of proteins within FAs regulates their activity and function. Vinculin binds different FA proteins to mediate distinct cellular functions, but how vinculin's interactions are spatiotemporally organized within FAs is unknown. Using interferometric photoactivation localization super-resolution microscopy to assay vinculin nanoscale localization and a FRET biosensor to assay vinculin conformation, we found that upward repositioning within the FA during FA maturation facilitates vinculin activation and mechanical reinforcement of FAs. Inactive vinculin localizes to the lower integrin signalling layer in FAs by binding to phospho-paxillin. Talin binding activates vinculin and targets active vinculin higher in FAs where vinculin can engage retrograde actin flow. Thus, specific protein interactions are spatially segregated within FAs at the nanoscale to regulate vinculin activation and function.

Corticosteroids (CS) act synergistically with thyroid hormone (TH) to accelerate amphibian metamorphosis. Earlier studies showed that CS increase nuclear 3,5,3’-triiodothyronine (T(3)) binding capacity in tadpole tail, and 5’ deiodinase activity in tadpole tissues, increasing the generation of T(3) from thyroxine (T(4)). In the present study we investigated CS synergy with TH by analyzing expression of key genes involved in TH and CS signaling using tadpole tail explant cultures, prometamorphic tadpoles, and frog tissue culture cells (XTC-2 and XLT-15). Treatment of tail explants with T(3) at 100 nM, but not at 10 nM caused tail regression. Corticosterone (CORT) at three doses (100, 500 and 3400 nM) had no effect or increased tail size. T(3) at 10 nM plus CORT caused tails to regress similar to 100 nM T(3). Thyroid hormone receptor beta (TRbeta) mRNA was synergistically upregulated by T(3) plus CORT in tail explants, tail and brain in vivo, and tissue culture cells. The activating 5’ deiodinase type 2 (D2) mRNA was induced by T(3) and CORT in tail explants and tail in vivo. Thyroid hormone increased expression of glucocorticoid (GR) and mineralocorticoid receptor (MR) mRNAs. Our findings support that the synergistic actions of TH and CS in metamorphosis occur at the level of expression of genes for TRbeta and D2, enhancing tissue sensitivity to TH. Concurrently, TH enhances tissue sensitivity to CS by upregulating GR and MR. Environmental stressors can modulate the timing of tadpole metamorphosis in part by CS enhancing the response of tadpole tissues to the actions of TH.

Synapses have undergone significant diversification and adaptation, contributing to the complexity of the central nervous system. Understanding their molecular architecture is essential for deciphering the brain's functional evolution. While nicotinic acetylcholine receptors (nAchRs) are widely distributed across metazoan brains, their associated protein networks remain poorly characterized. Using in vivo proximity labeling, we generated proteomic maps of subunit-specific nAchR interactomes in developing and mature brains. Our findings reveal a developmental expansion and reconfiguration of the nAchR interactome. Proteome profiling with genetic perturbations showed that removing individual nAchR subunits consistently triggers compensatory shifts in receptor subtypes, highlighting mechanisms of synaptic plasticity. We also identified the Rho-GTPase regulator Still life (Sif) as a key organizer of cholinergic synapses, with loss of Sif disrupting their molecular composition and structural integrity. These results provide molecular insights into the development and plasticity of central cholinergic synapses, advancing our understanding of synaptic identity conservation and divergence.

The tobacco hornworm Manduca sexta, like many holometabolous insects, makes two versions of its thoracic legs. The simple legs of the larva are formed during embryogenesis, but then are transformed into the more complex adult legs at metamorphosis. To elucidate the molecular patterning mechanism underlying this biphasic development, we examined the expression patterns of five genes known to be involved in patterning the proximal-distal axis in insect legs. In the developing larval leg of Manduca, the early patterning genes Distal-less and Extradenticle are already expressed in patterns comparable to the adult legs of other insects. In contrast, Bric-a-brac and dachshund are expressed in patterns similar to transient patterns observed during early stages of leg development in Drosophila. During metamorphosis of the leg, the two genes finally develop mature expression patterns. Our results are consistent with the hypothesis that the larval leg morphology is produced by a transient arrest in the conserved adult leg patterning process in insects. In addition, we find that, during the adult leg development, some cells in the leg express the patterning genes de novo suggesting that the remodeling of the leg involves changes in the patterning gene regulation.

Mutualism with ants is suspected to be a highly labile trait within homopteran evolution. We used molecular phylogenetic evidence to test whether the mutualism has multiple origins within a single aphid genus. We constructed a molecular phylogeny of 15 Chaitophorus Koch (Hemiptera: Aphidoidea) species, using mitochondrial cytochrome oxidase I and II sequences. Ant tending evolved, or was lost, at least five times during Chaitophorus evolution. Parametric bootstrapping rejected the hypothesis of a single origin of ant tending in this genus. Further, the Chaitophorus made at least two host genus switches from poplars (Populus) to willow (Salix), and four switches in feeding position, from leaf feeding to stem feeding or vice versa. This is the first phylogenetic confirmation that ant tending is an evolutionarily labile trait in aphids.

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.