At the blood-tissue interface, vasculature luminal surface is critical for molecular transport, signaling transduction, and cell extravasation. Here, we present a method for proteomic profiling of the vasculature luminal surface in vivo, broadly applicable to any vertebrate. Quantitative mass spectrometry revealed the luminal surface proteome of the mouse brain vasculature and its temporal evolution from development to aging. In vivo genetic perturbation found that the arginine transporter SLC7A1 and the nitric oxide synthase NOS3 are needed for blood-brain barrier integrity in neonatal but not adult mice, whereas the hyaluronan degradation enzyme HYAL2 safeguards the barrier throughout the lifespan. By characterizing the proteomic dynamics of the vasculature luminal surface, the study links the metabolism of nitric oxide and hyaluronan to blood-brain barrier integrity.

Isocitrate lyase 2 (ICL2) from Mycobacterium tuberculosis undergoes dramatic conformational rearrangements upon binding to the allosteric effector acetyl-CoA. Time-resolved cryo-EM captured conformational states along the ICL2 activation trajectory, revealing how acetyl-CoA binding at the allosteric sites leads to asymmetric, half-of-site activity at the catalytic centres. These findings support a conformational selection model of allostery, whereby acetyl-CoA binding shifts the pre-existing equilibrium towards an active state of the enzyme.

Connectomics has become essential for the study of brain function, yet for most research groups it remains prohibitively costly in imaging time, data storage, and analysis. Here, we present an imaging, processing, and analysis pipeline for multi-resolution image acquisition and circuit reconstruction. Applied to the central complex of six insect species, we were able to obtain global projectomes at cellular resolution (40-50 nm) with embedded local connectomes describing key computational compartments at synaptic resolution (8-12 nm). We provide standardized protocols for volume EM sample preparation, image acquisition and image alignment, combined with existing methods for µCT block trimming, automatic segmentation, synapse detection, collaborative skeleton tracing with CATMAID, and segmentation proofreading via CAVE. We validated our workflow by reconstructing head direction cells across all six insect species, which revealed deep conservation at the level of cell types, cell numbers and projection patterns, while also revealing circuit level specializations. Overall, our pipeline democratizes comparative connectomics by making this method accessible for small research groups with modest resources.

Regulation of food intake in mammals is complex and controlled by an interplay between hedonic and homeostatic signals, including hormones like leptin, which senses fat storage and suppresses food intake. lack leptin and leptin receptors but still exhibit controlled eating. Here, we show that in eating can be regulated by a balance between saturated and monounsaturated fatty acids interacting with transcriptional pathways regulating lipid synthesis, c-AMP response element binding protein and AMP kinase. This effect is mediated at the endoplasmic reticulum through formation of phospholipids and activation of the IRE-1 sensor in the nervous system, which controls behavior through neuronal serotonin and the G-protein-coupled ligand/receptor pair PDF-1/PDFR-1. We show that this peptide/receptor pair may be an ancestral precursor of the whole family of GLP-1/GIP-related peptides and their receptors. Indeed, administration of a 37 amino acid peptide derived from PDF-1 resulted in a reduction in body weight and improved insulin sensitivity in mice. In worms, signaling through this pathway induced food-leaving behavior on concentrated food and roaming behavior on dispersed food, a state we have termed "food-apathy," paralleling pharmacologic effects of GLP-1/GIP-related peptides in humans. These findings highlight the potential evolutionary origin of this family of hormones and their receptors, and its link to metabolic and neuronal responses in control of feeding behavior.

The distribution of mitochondrial DNA-containing nucleoids is essential for mitochondrial function and genome inheritance; however, no known mechanisms can explain nucleoid segregation or their regular positioning. In this work, we found that mitochondria frequently undergo a reversible biophysical instability termed "pearling," transforming from a tubular into a regularly spaced beads morphology. Physiological pearling imposed a characteristic length scale and simultaneously mediated nucleoid disaggregation and established internucleoid distancing with high precision. Pearling onset was triggered by calcium influx, whereas the density of lamellar cristae invaginations modulated pearling prevalence and preserved nucleoid spacing following recovery. The dysregulation of mitochondrial calcium influx or inner membrane cristae integrity caused aberrant nucleoid clustering. Our results identify pearling as a mechanism governing nucleoid distribution and inheritance and offer insights into its regulation.

Cells work together to accomplish complex tasks. For example, both neutrophils and Dictyostelid collectives use self-generated multicellular signaling gradients to coordinate aggregation over large areas through local interactions. However, these aggregation programs occur for different reasons that necessitate different implementations. Dictyostelids are soil-dwelling amoeba that aggregate when starving to facilitate dispersal to new locations. These aggregates do not require specific locations or group sizes. In contrast, neutrophils are innate immune cells that collectively migrate to sites of injury and infection. These swarms need to occur in specific locations and must be constrained in size to avoid collateral damage to the host. Here, we review how these evolutionarily divergent systems sculpt long-range gradients at the molecular and cellular levels, discussing their similarities and differences in light of their distinctive goals. Convergence on self-generated gradients for aggregation despite different goals suggests that it is an optimal strategy to bring individuals together in complex environments.

Foraging, defined as the search for food to sustain one's energetic needs, is a fundamental behavior performed by almost all animals to survive in their environment. Foraging involves a variety of physiological processes, including metabolic and cognitive computations. In this review, we provide a brief historical overview of foraging and foraging theory, highlight recent insights into the neural mechanisms of foraging, and contextualize them within the broader neuroscience literature. We present an integrative approach to foraging that combines neural mechanisms of foraging with ecological, behavioral, and physiological mechanisms.

Calcium imaging with miniature endoscopes has become an essential tool in neuroscience, but conventional miniscopes typically record signals from only a single calcium indicator. Here, we present a dual-color miniature endoscope (miniscope) that enables simultaneous calcium imaging from two neuronal populations using spectrally distinct genetically encoded indicators. In freely moving mice, we used this system to record activity from striatal neurons of the direct (dSPN) and indirect (iSPN) pathways. We showed that dSPNs were activated earlier than iSPNs during contraversive movements, with dSPNs preferentially active during acceleration and iSPNs during deceleration. During ipsiversive turns, however, this temporal relationship was reversed. These findings indicate that dSPNs and iSPNs are not concurrently active, but instead exhibit complementary, direction-dependent dynamics that govern movement velocity. Our dual-color miniscope provides a compact, cost-effective platform for simultaneous two-population imaging, offering new opportunities to dissect coordinated activity across neural circuits in freely behaving animals.

Many insects manipulate plants by injecting effector proteins. In one extreme example of this molecular “hijacking”, Hormaphis cornu aphids inject bicycle proteins into Hamamelis virginiana (Witch Hazel), contributing to the development of novel organs called galls. Bicycle proteins share no amino acid sequence similarity with proteins of known function. Here, we report the crystal structures of two divergent bicycle proteins. Both proteins contain saposin-like folds: one with multiple disulfide bonds exhibits a helix swap; the other has no disulfide bonds and possesses two tandem domains. To explore the structural evolution of bicycle proteins, we predicted bicycle protein structures with Alphafold2 (AF2). While AF2 did not recover the two experimental structures using existing databases, it succeeded after we provided multiple sequence alignments (MSAs) containing protein sequences encoded in new genome sequences from closely related aphid species. Using this customized approach at scale, we generated 2400 high-confidence predictions for bicycle proteins from seven aphid species. This dataset revealed that bicycle proteins without cysteines are outliers in fold space and appear to have evolved from ancestral proteins with disulfide-bonded saposin-like folds. While all bicycle proteins contain predicted saposin-like folds, they display a vast diversity of structural and physicochemical properties. While this diversity thwarts prediction of conserved functions encoded in structure, it suggests that bicycle proteins have evolved to target diverse plant processes and/or to evade plant immune surveillance.Significance statement Parasites introduce specialized “effector” proteins into hosts, both to suppress host immunity and to release nutrients. The molecular functions and structures of most effector proteins are unknown. Effector proteins often evolve rapidly and share no similarity with proteins of known function. Here, we demonstrate that machine learning algorithms can accurately predict the structures of aphid “bicycle” effector proteins when supplemented with data from closely related species. We exploit this finding to generate predictions of 2400 bicycle protein structures. These proteins exploit a common motif, yet exhibit diverse structures that form distinct structural clusters. Despite the clustering of these proteins in structure space, they occupy a nearly uniformly physicochemical space, suggesting that they encode a large diversity of molecular functions.

NPAS4 is an activity-dependent transcription factor that, in CA1 of the hippocampus, regulates inhibitory synapses made onto the active pyramidal neuron. In principle, NPAS4 thereby allows the past activity of a neuron to influence how it encodes information, although this has not yet been demonstrated. Here, we generated a sparse, CA1-specific knockout (KO) of NPAS4 in the mouse hippocampus and used optogenetic tagging to identify KO neurons in vivo. Recordings from intermingled wild-type (WT) and KO neurons in awake behaving animals revealed that NPAS4 deletion degrades spatial representations and temporal precision of spiking: KO neurons exhibited larger place fields with reduced in-field firing and increased out-of-field firing, less stable place fields, reduced coupling to local field potential theta oscillations, and diminished phase precession. These findings demonstrate that NPAS4 plays a crucial role in refining the spatial and temporal properties of CA1 pyramidal neuron spikes, which themselves are thought to be fundamental building blocks of more complex processes such as learning and memory.