Glucose is arguably the most important molecule in metabolism, and its dysregulation underlies diabetes. We describe a family of single-wavelength genetically encoded glucose sensors with a high signal-to-noise ratio, fast kinetics, and affinities varying over four orders of magnitude (1 μM to 10 mM). The sensors allow mechanistic characterization of glucose transporters expressed in cultured cells with high spatial and temporal resolution. Imaging of neuron/glia co-cultures revealed ∼3-fold faster glucose changes in astrocytes. In larval Drosophila central nervous system explants, intracellular neuronal glucose fluxes suggested a rostro-caudal transport pathway in the ventral nerve cord neuropil. In zebrafish, expected glucose-related physiological sequelae of insulin and epinephrine treatments were directly visualized. Additionally, spontaneous muscle twitches induced glucose uptake in muscle, and sensory and pharmacological perturbations produced large changes in the brain. These sensors will enable rapid, high-resolution imaging of glucose influx, efflux, and metabolism in behaving animals.

Executing learned motor behaviors often requires the transformation of sensory cues into patterns of motor commands that generate appropriately timed actions. The cerebellum and thalamus are two key areas involved in shaping cortical output and movement, but the contribution of a cerebellar-thalamocortical pathway to voluntary movement initiation remains poorly understood. Here, we investigated how an auditory "go cue" transforms thalamocortical activity patterns and how these changes relate to movement initiation. Population responses in dentate/interpositus-recipient regions of motor thalamus reflect a time-locked increase in activity immediately prior to movement initiation that is temporally uncoupled from the go cue, indicative of a fixed-latency feedforward motor timing signal. Blocking cerebellar or motor thalamic output suppresses movement initiation, while stimulation triggers movements in a behavioral context-dependent manner. Our findings show how cerebellar output, via the thalamus, shapes cortical activity patterns necessary for learned context-dependent movement initiation.

In severe viral pneumonia, including Coronavirus disease 2019 (COVID-19), the viral replication phase is often followed by hyperinflammation, which can lead to acute respiratory distress syndrome, multi-organ failure, and death. We previously demonstrated that alpha-1 adrenergic receptor (⍺-AR) antagonists can prevent hyperinflammation and death in mice. Here, we conducted retrospective analyses in two cohorts of patients with acute respiratory distress (ARD, n = 18,547) and three cohorts with pneumonia (n = 400,907). Federated across two ARD cohorts, we find that patients exposed to ⍺-AR antagonists, as compared to unexposed patients, had a 34% relative risk reduction for mechanical ventilation and death (OR = 0.70, p = 0.021). We replicated these methods on three pneumonia cohorts, all with similar effects on both outcomes. All results were robust to sensitivity analyses. These results highlight the urgent need for prospective trials testing whether prophylactic use of ⍺-AR antagonists ameliorates lower respiratory tract infection-associated hyperinflammation and death, as observed in COVID-19.

For a more complete understanding of molecular mechanisms, it is important to study macromolecules and their assemblies in the broader context of the cell. This context can be visualized at nanometer resolution in three dimensions (3D) using electron cryo-tomography, which requires tilt series to be recorded and computationally aligned, currently limiting throughput. Additionally, the high-resolution signal preserved in the raw tomograms is currently limited by a number of technical difficulties, leading to an increased false-positive detection rate when using 3D template matching to find molecular complexes in tomograms. We have recently described a 2D template matching approach that addresses these issues by including high-resolution signal preserved in single-tilt images. A current limitation of this approach is the high computational cost that limits throughput. We describe here a GPU-accelerated implementation of 2D template matching in the image processing software TEM that allows for easy scaling and improves the accessibility of this approach. We apply 2D template matching to identify ribosomes in images of frozen-hydrated cells with high precision and sensitivity, demonstrating that this is a versatile tool for visual proteomics and structure determination. We benchmark the results with 3D template matching of tomograms acquired on identical sample locations and identify strengths and weaknesses of both techniques, which offer complementary information about target localization and identity.

Fold-switching proteins challenge the one-sequence-one-structure paradigm by adopting multiple stable folds. Nevertheless, it is uncertain whether fold switchers are naturally pervasive or rare exceptions to the well-established rule. To address this question, we developed a predictive method and applied it to the NusG superfamily of >15,000 transcription factors. We predicted that a substantial population (25%) of the proteins in this family switch folds. Circular dichroism and nuclear magnetic resonance spectroscopies of 10 sequence-diverse variants confirmed our predictions. Thus, we leveraged family-wide predictions to determine both conserved contacts and taxonomic distributions of fold-switching proteins. Our results indicate that fold switching is pervasive in the NusG superfamily and that the single-fold paradigm significantly biases structure-prediction strategies.

Hippocampal place cells contribute to mammalian spatial navigation and memory formation. Numerous models have been proposed to explain the location-specific firing of this cognitive representation, but the pattern of excitatory synaptic input leading to place firing is unknown, leaving no synaptic-scale explanation of place coding. Here we used resonant scanning two-photon microscopy to establish the pattern of synaptic glutamate input received by CA1 place cells in behaving mice. During traversals of the somatic place field, we found increased excitatory dendritic input, mainly arising from inputs with spatial tuning overlapping the somatic field, and functional clustering of this input along the dendrites over ~10 µm. These results implicate increases in total excitatory input and co-activation of anatomically clustered synaptic input in place firing. Since they largely inherit their fields from upstream synaptic partners with similar fields, many CA1 place cells appear to be part of multi-brain-region cell assemblies forming representations of specific locations.

The measurement of ion concentrations and fluxes inside living cells is key to understanding cellular physiology. Fluorescent indicators that can infiltrate and provide intel on the cellular environment are critical tools for biological research. Developing these molecular informants began with the seminal work of Racker and colleagues ( (1979) 18, 2210), who demonstrated the passive loading of fluorescein in living cells to measure changes in intracellular pH. This work continues, employing a mix of old and new tradecraft to create innovative agents for monitoring ions inside living systems.

Neuroendocrine systems in animals maintain organismal homeostasis and regulate stress response. Although a great deal of work has been done on the neuropeptides and hormones that are released and act on target organs in the periphery, the synaptic inputs onto these neuroendocrine outputs in the brain are less well understood. Here, we use the transmission electron microscopy reconstruction of a whole central nervous system in the larva to elucidate the sensory pathways and the interneurons that provide synaptic input to the neurosecretory cells projecting to the endocrine organs. Predicted by network modeling, we also identify a new carbon dioxide-responsive network that acts on a specific set of neurosecretory cells and that includes those expressing corazonin (Crz) and diuretic hormone 44 (Dh44) neuropeptides. Our analysis reveals a neuronal network architecture for combinatorial action based on sensory and interneuronal pathways that converge onto distinct combinations of neuroendocrine outputs.

The ability to adjust one's behavioral strategy in complex environments is at the core of cognition. Doing so efficiently requires monitoring the reliability of the ongoing strategy and, when appropriate, switching away from it to evaluate alternatives. Studies in humans and non-human primates have uncovered signals in the anterior cingulate cortex (ACC) that reflect the pressure to switch away from the ongoing strategy, whereas other ACC signals relate to the pursuit of alternatives. However, whether these signals underlie computations that actually underpin strategy switching or merely reflect tracking of related variables remains unclear. Here we provide causal evidence that the rodent ACC actively arbitrates between persisting with the ongoing behavioral strategy and temporarily switching away to re-evaluate alternatives. Furthermore, by individually perturbing distinct output pathways, we establish that the two associated computations-determining whether to switch strategy and committing to the pursuit of a specific alternative-are segregated in the ACC microcircuitry.

Decisions are held in memory until enacted, which makes them potentially vulnerable to distracting sensory input. Gating of information flow from sensory to motor areas could protect memory from interference during decision-making, but the underlying network mechanisms are not understood. Here, we trained mice to detect optogenetic stimulation of the somatosensory cortex, with a delay separating sensation and action. During the delay, distracting stimuli lost influence on behavior over time, even though distractor-evoked neural activity percolated through the cortex without attenuation. Instead, choice-encoding activity in the motor cortex became progressively less sensitive to the impact of distractors. Reverse engineering of neural networks trained to reproduce motor cortex activity revealed that the reduction in sensitivity to distractors was caused by a growing separation in the neural activity space between attractors that encode alternative decisions. Our results show that communication between brain regions can be gated via attractor dynamics, which control the degree of commitment to an action.