bioRxiv : the preprint server for biology最新文献

Spreading depolarization (SD) is a slowly propagating wave of massive cellular depolarization that transiently impairs the function of affected brain regions. While SD typically arises as an isolated hemispheric event, we previously reported that reducing M-type potassium current (I_KM) by ablation of Kcnq2 in forebrain excitatory neurons results in tightly coupled spontaneous bilateral seizure-SD complexes in the awake mouse cortex. Here we find that enhanced persistent Na⁺ current due to gain-of-function (GOF) mutations in Scn8a (N1768D/+, hereafter D/+) produces a similar compound cortical excitability phenotype. Chronic DC-band EEG recording detected spontaneous bilateral seizure-SD complexes accompanied by seizures with a profound tonic motor component, which occur predominantly during the light phase and were detected at ages between P33-100. Laser speckle contrast imaging of cerebral blood flow dynamics resolved SD as a bilateral wave of hypoperfusion and subsequent hour-lasting hypoperfusion in Scn8a ^D/+ cortex in awake head-restrained mice evoked by a PTZ injection. Subcortical recordings in freely moving mice revealed that approximately half of the spontaneous cortical seizure-SD complexes arose with a concurrent SD-like depolarization in the thalamus and delayed depolarization in the striatum. In contrast, SD-like DC potential shifts were rarely detected in the hippocampus or upper pons. Consistent with the high spontaneous incidence in vivo, cortical slices from Scn8a ^D/+ mice showed a raised SD susceptibility, and pharmacological inhibition of persistent Na⁺ current (I_NaP), which is enhanced in Scn8a ^D/+ neurons, inhibited SD generation in cortical slices ex vivo as well as in head-fixed mice in vivo, indicating that I_NaP contributes to SD susceptibility. Ex vivo Ca²⁺ imaging studies using acute brain slices expressing genetic Ca²⁺ sensor (Thy1-GCAMP6s) demonstrated that pharmacological activation of I_KM suppressed Ca²⁺ spikes and SD, whereas an I_KM inhibitor strongly increased the frequency of hippocampal Ca²⁺ spikes in Scn8a ^D/+, but not WT slices, suggesting that I_KM restrains the Scn8a GOF hyperexcitability. Together, our study identifies a cortical SD phenotype in Scn8a GOF mice shared with the Kcnq2-cKO model of developmental epileptic encephalopathy, and reveals that an imbalance of non-inactivating inward and outward tonic membrane currents bidirectionally modulates spatiotemporal SD susceptibility.

A key goal of the nervous system in young animals is to learn motor skills. Songbirds learn to sing as juveniles, providing a unique opportunity to identify the neural correlates of skill acquisition. Prior studies have shown that spike rate variability in vocal motor cortex decreases substantially during song acquisition, suggesting a transition from rate-based neural control to the millisecond-precise motor codes known to underlie adult vocal performance. By distinguishing how the ensemble of spike patterns fired by cortical neurons (the "neural vocabulary") and the relationship between spike patterns and song acoustics (the "neural code") change during song acquisition, we quantified how vocal control changes across learning in juvenile Bengalese finches. We found that despite the expected drop in rate variability (a learning-related change in spike vocabulary), the precision of the neural code in the youngest singers is the same as in adults, with 1-2 ms variations in spike timing transduced into quantifiably different behaviors. In contrast, fluctuations in firing rates on longer timescales fail to affect the motor output in both juvenile and adult animals. The consistent presence of millisecond-scale motor coding during changing levels of spike rate and behavioral variability suggests that learning-related changes in cortical activity reflect the brain's changing its spiking vocabulary to better match the underlying motor code, rather than a change in the precision of the code itself.

Recent advances in computational methods have led to considerable progress in the design of self-assembling protein nanoparticles. However, nearly all nanoparticles designed to date exhibit strict point group symmetry, with each subunit occupying an identical, symmetrically related environment. This limits the structural diversity that can be achieved and precludes anisotropic functionalization. Here, we describe a general computational strategy for designing multi-component bifaceted protein nanomaterials with two distinctly addressable sides. The method centers on docking pseudosymmetric heterooligomeric building blocks in architectures with dihedral symmetry and designing an asymmetric protein-protein interface between them. We used this approach to obtain an initial 30-subunit assembly with pseudo-D5 symmetry, and then generated an additional 15 variants in which we controllably altered the size and morphology of the bifaceted nanoparticles by designing de novo extensions to one of the subunits. Functionalization of the two distinct faces of the nanoparticles with de novo protein minibinders enabled specific colocalization of two populations of polystyrene microparticles coated with target protein receptors. The ability to accurately design anisotropic protein nanomaterials with precisely tunable structures and functions could be broadly useful in applications that require colocalizing two or more distinct target moieties.

The progression of metabolic-dysfunction-associated steatotic liver disease (MASLD) to metabolic-dysfunction-associated steatohepatitis (MASH) involves complex alterations in both liver-autonomous and systemic metabolism that influence the liver's balance of fat accretion and disposal. Here, we quantify the relative contribution of hepatic oxidative pathways to liver injury in MASLD-MASH. Using NMR spectroscopy, UHPLC-MS, and GC-MS, we performed stable-isotope tracing and formal flux modeling to quantify hepatic oxidative fluxes in humans across the spectrum of MASLD-MASH, and in mouse models of impaired ketogenesis. We found in humans with MASH, that liver injury correlated positively with ketogenesis and total fat oxidation, but not with turnover of the tricarboxylic acid cycle. The use of loss-of-function mouse models demonstrated that disruption of mitochondrial HMG-CoA synthase (HMGCS2), the rate-limiting step of ketogenesis, impairs overall hepatic fat oxidation and induces a MASLD-MASH-like phenotype. Disruption of mitochondrial β-hydroxybutyrate dehydrogenase (BDH1), the terminal step of ketogenesis, also impaired fat oxidation, but surprisingly did not exacerbate steatotic liver injury. Taken together, these findings suggest that quantifiable variations in overall hepatic fat oxidation may not be a primary determinant of MASLD-to-MASH progression, but rather, that maintenance of hepatic ketogenesis could serve a protective role through additional mechanisms that extend beyond quantified overall rates of fat oxidation.

A cell's global physical state is characterized by its volume and dry mass. The ratio of cell mass to volume is the cell mass density (CMD), which is also a measure of macromolecular crowding and concentrations of all proteins. Using the Fluorescence eXclusion method (FXm) and Quantitative Phase Microscopy (QPM), we investigate CMD dynamics after exposure to sudden media osmolarity change. We find that while the cell volume and mass exhibit complex behavior after osmotic shock, CMD follows a straightforward monotonic recovery in 48 hours. The recovery is cell-cycle independent and relies on a coordinated adjustment of protein synthesis and volume growth rates. Surprisingly, we find that the protein synthesis rate decreases when CMD increases. This result is explained by CMD-dependent nucleoplasm-cytoplasm transport, which serves as negative regulatory feedback on CMD. The Na+/H+ exchanger NHE plays a role in regulating CMD by affecting both protein synthesis and volume change. Taken together, we reveal that cells possess a robust control system that actively regulates CMD during environmental change.

Humans and other social animals can represent and navigate complex networks of social relationships in ways that are suggestive of representation and navigation in space. There is some evidence that cortical regions initially required for processing space have been adapted to include processing of social information. One candidate region for supporting both spatial and social information processing is the posterior parietal cortex (PPC). We examined the hypothesis that rats can transfer or generalize distance information across spatial and social domains and that this phenomenon requires the PPC. In a novel apparatus, rats learned to discriminate two conspecifics positioned at different spatial distances (near vs. far) in a goal-driven paradigm. Following spatial learning, subjects were tested on probe trials in which spatial distance was replaced with social distance (cagemate vs. less familiar conspecific). The PPC was chemogenetically inactivated during a subset of probe sessions. We predicted that, in control probe trials, subjects would select conspecifics whose social distance matched the previously learned spatial distance. That is, if trained on the near distance, the rat would choose the highly familiar cagemate, and if trained on the far distance, the rat would choose the less familiar conspecific. Subjects learned to discriminate conspecifics based on spatial distance in our goal-driven paradigm. Moreover, choice for the appropriate social distance in the first probe session was significantly higher than chance. This result suggests that rats transferred learned spatial information to social contexts. Contrary to our predictions, PPC inactivation did not impair spatial to social information transfer. Possible reasons are discussed. To our knowledge, this is the first study to provide evidence that spatial and social distance are processed by shared cognitive mechanisms in the rat model.

Circadian rhythms influence various physiological and behavioral processes such as sleep-wake cycles, hormone secretion, and metabolism. In Drosophila, an important set of circadian output neurons are called pars intercerebralis (PI) neurons, which receive input from specific clock neurons called DN1. These DN1 neurons can further be subdivided into functionally and anatomically distinctive anterior (DN1a) and posterior (DN1p) clusters. The neuropeptide diuretic hormones 31 (Dh31) and 44 (Dh44) are the insect neuropeptides known to activate PI neurons to control activity rhythms. However, the neurophysiological basis of how Dh31 and Dh44 affect circadian clock neural coding mechanisms underlying sleep in Drosophila is not well understood. Here, we identify Dh31/Dh44-dependent spike time precision and plasticity in PI neurons. We first find that a mixture of Dh31 and Dh44 enhanced the firing of PI neurons, compared to the application of Dh31 alone and Dh44 alone. We next find that the application of synthesized Dh31 and Dh44 affects membrane potential dynamics of PI neurons in the precise timing of the neuronal firing through their synergistic interaction, possibly mediated by calcium-activated potassium channel conductance. Further, we characterize that Dh31/Dh44 enhances postsynaptic potentials in PI neurons. Together, these results suggest multiplexed neuropeptide-dependent spike time precision and plasticity as circadian clock neural coding mechanisms underlying sleep in Drosophila.

Amphipathic helices (AHs) are ubiquitous protein motifs that modulate targeting to organellar membranes by sensing differences in bulk membrane properties. However, the adaptation between membrane-targeting AHs and the nuclear membrane environment that surrounds the genome is poorly understood. Here, we computationally screened for candidate AHs in a curated list of characterized and putative human inner nuclear membrane (INM) proteins. Cell biological and in vitro experimental assays combined with computational calculations demonstrated that AHs detect lipid packing defects over electrostatics to bind to the INM, indicating that the INM is loosely packed under basal conditions. Membrane tension resulting from hypotonic shock further promoted AH binding to the INM, whereas cell-substrate stretch did not enhance recruitment of membrane tension-sensitive AHs. Together, our work demonstrates the rules driving lipid-protein interactions at the INM, and its implications in the response of the nucleus to different stimuli.

Familial dysautonomia (FD) is a fatal autosomal recessive congenital neuropathy caused by a T-to-C mutation in intron 20 of the Elongator acetyltransferase complex subunit 1 (ELP1) gene, which causes tissue-specific skipping of exon 20 and reduction of ELP1 protein. Here, we developed a base editor (BE) approach to precisely correct this mutation. By optimizing Cas9 variants and screening multiple gRNAs, we identified a combination that was able to promote up to 70% on-target editing in HEK293T cells harboring the ELP1 T-to-C mutation. These editing levels were sufficient to restore exon 20 inclusion in the ELP1 transcript. Moreover, we optimized an engineered dual intein-split system to deliver these constructs in vivo. Mediated by adeno-associated virus (AAV) delivery, this BE strategy effectively corrected the liver and brain ELP1 splicing defects in a humanized FD mouse model carrying the ELP1 T-to-C mutation and rescued the FD phenotype in iPSC-derived sympathetic neurons. Importantly, we observed minimal off-target editing demonstrating high levels of specificity with these optimized base editors. These findings establish a novel and highly precise BE-based therapeutic approach to correct the FD mutation and associated splicing defects and provide the foundation for the development of a transformative, permanent treatment for this devastating disease.

A challenge in sensory neuroscience is understanding how populations of neurons operate in concert to represent diverse stimuli. To meet this challenge, we have created "encoding manifolds" that reveal the overall responses of brain areas to diverse stimuli with the resolution of individual neurons and their response dynamics. Here we use encoding manifold to compare the population-level encoding of primary visual cortex (VISp) with five higher visual areas (VISam, VISal, VISpm, VISlm, and VISrl). We used data from the Allen Institute Visual Coding-Neuropixels dataset from the mouse. We show that the encoding manifold topology computed only from responses to grating stimuli is continuous, for V1 and for higher visual areas, with smooth coordinates spanning it that include orientation selectivity and firing-rate magnitude. Surprisingly, the manifolds for each visual area revealed novel relationships between how natural scenes are encoded relative to static gratings-a relationship that was conserved across visual areas. Namely, neurons preferring natural scenes preferred either low or high spatial frequency gratings, but not intermediate ones. Analyzing responses by cortical layer reveals a preference for gratings concentrated in layer 6, whereas preferences for natural scenes tended to be higher in layers 2/3 and 4. The results reveal how machine learning approaches can be used to organize and visualize the structure of sensory coding, thereby revealing novel relationships within and across brain areas and sensory stimuli.