bioRxiv : the preprint server for biology最新文献

Rates of lactate production and consumption reflect the metabolic state of many cell types, including neurons. Here, we investigate the effects of nutrient deprivation on lactate dynamics in Drosophila glutamatergic neurons by leveraging the limiting effects of the diffusion barrier surrounding cells in culture. We found that neurons constitutively consume lactate when availability of trehalose, the glucose disaccharide preferred by insects, is limited by the diffusion barrier. Acute mechanical disruption of the barrier reduced this reliance on lactate. Through kinetic modeling and experimental validation, we demonstrate that neuronal lactate consumption rates correlate inversely with their mitochondrial density. Further, we found that lactate levels in neurons exhibited temporal correlations that allowed prediction of cytosolic lactate dynamics after the disruption of the diffusion barrier from pre-perturbation lactate fluctuations. Collectively, our findings reveal the influence of diffusion barriers on neuronal metabolic preferences, and demonstrate the existence of temporal correlations between lactate dynamics under conditions of nutrient deprivation and those evoked by the subsequent restoration of nutrient availability.

Small extracellular vesicles (sEVs) are heterogeneous biological vesicles released by cells under both physiological and pathological conditions. Due to their potential as valuable diagnostic and prognostic biomarkers in human blood, there is a pressing need to develop effective methods for isolating high-purity sEVs from the complex milieu of blood plasma, which contains abundant plasma proteins and lipoproteins. Size exclusion chromatography (SEC) and density gradient ultracentrifugation (DGUC) are two commonly employed isolation techniques that have shown promise in addressing this challenge. In this study, we aimed to determine the optimal combination and sequence of SEC and DGUC for isolating sEVs from small plasma volumes, in order to enhance both the efficiency and purity of the resulting isolates. To achieve this, we compared sEV isolation using two combinations: SEC-DGUC and DGUC-SEC, from unit volumes of 500 μl plasma. Both protocols successfully isolated high-purity sEVs; however, the SEC-DGUC combination yielded higher sEV protein and RNA content. We further characterized the isolated sEVs obtained from the SEC-DGUC protocol using flow cytometry and mass spectrometry to assess their quality and purity. In conclusion, the optimized SEC-DGUC protocol is efficient, highly reproducible, and well-suited for isolating high-purity sEVs from small blood volumes.

Neurodevelopmental disorders disproportionately affect males compared to females. The biological mechanisms of this male susceptibility or female protection have not been identified. There is evidence that fetal/neonatal gonadal hormones, which play a pivotal role in many aspects of development, may contribute. Here, we investigate the effects of excess testosterone during a critical period of sex-specific brain organization on social approach and fear learning behaviors in C57BL/6J wild-type mice. Male, but not female, mice treated with testosterone on the day of birth (PN0) exhibited decreased social approach as juveniles and decreased contextual fear memory as adults, compared to vehicle-treated controls. These deficits were not driven by anxiety-like behavior or changes in locomotion or body weight. Mice treated with the same dose of testosterone on postnatal day 18 (PN18), which is outside of the critical period of brain masculinization, did not demonstrate impairments compared to the vehicle group. These findings indicate that excess testosterone during a critical period of early development, but not shortly after, induces long-term deficits relevant to the male sex bias in neurodevelopmental disorders.

Peripheral nerve injuries are common, and there is a critical need for the development of novel treatments to complement surgical repair. Conditioning electrical stimulation (CES) is a novel variation of the well-studied perioperative electrical stimulation treatment paradigm. CES is a clinically attractive alternative because of its ability to be performed at the bedside prior to a scheduled nerve repair surgery. Although 60 minutes of CES has been shown to enhance motor and sensory axon regeneration, the effects of CES on sympathetic regeneration are unknown. We investigated how two clinically relevant CES paradigms (10 minutes and 60 minutes) impact sympathetic axon regeneration and distal target reinnervation. Our results indicate that the growth of sympathetic axons is inhibited by CES at acute time points, and at a longer survival time point post-injury, there is no difference between sham CES and the CES groups. We conclude sympathetic axons may retain some regenerative ability, but no enhancement is exhibited after CES, which may be accounted for by the inability of the electrical stimulation paradigm to recruit the small-caliber sympathetic axons into activity. Furthermore, 10-minute CES did not enhance motor and sensory regeneration with a direct repair, and neither 60-minute nor 10-minute CES enhanced motor and sensory regeneration through a graft. Further studies will be needed to optimize electrical stimulation parameters to enhance the regeneration of all neuron types.

Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder characterized by deficits in social interactions, repetitive behaviors, and hyper- or hyposensitivity to sensory stimuli. The mechanisms underlying the emergence of sensory features in ASD are not fully understood, but recent studies in rodent models highlight that these may result from differences in primary sensory neurons themselves. We examined sensory behaviors in a Pten haploinsufficient mouse model ( Pten ^Het ) for syndromic ASD and identified elevated responses to mechanical stimuli and a higher threshold to thermal responses. Transcriptomic and in vivo anatomical analysis identified alterations in subtype-specific markers of primary somatosensory neurons in Pten ^Het dorsal root ganglia (DRG). These defects emerge early during DRG development and involve dysregulation of multiple signaling pathways downstream of Pten . Finally, we show that mice harboring an ASD-associated mutation ( Pten ^Y69H ) also show altered expression of somatosensory neuron subtype-specific markers. Together, these results show that precise levels of Pten are required for proper somatosensory development and provide insight into the molecular and cellular basis of sensory abnormalities in a model for syndromic ASD.

The principle of efficient coding posits that sensory cortical networks are designed to encode maximal sensory information with minimal metabolic cost. Despite the major influence of efficient coding in neuroscience, it has remained unclear whether fundamental empirical properties of neural network activity can be explained solely based on this normative principle. Here, we derive the structural, coding, and biophysical properties of excitatory-inhibitory recurrent networks of spiking neurons that emerge directly from imposing that the network minimizes an instantaneous loss function and a time-averaged performance measure enacting efficient coding. We assumed that the network encodes a number of independent stimulus features varying with a time scale equal to the membrane time constant of excitatory and inhibitory neurons. The optimal network has biologically-plausible biophysical features, including realistic integrate-and-fire spiking dynamics, spike-triggered adaptation, and a non-specific excitatory external input. The excitatory-inhibitory recurrent connectivity between neurons with similar stimulus tuning implements feature-specific competition, similar to that recently found in visual cortex. Networks with unstructured connectivity cannot reach comparable levels of coding efficiency. The optimal ratio of excitatory vs inhibitory neurons and the ratio of mean inhibitory-to-inhibitory vs excitatory-to-inhibitory connectivity are comparable to those of cortical sensory networks. The efficient network solution exhibits an instantaneous balance between excitation and inhibition. The network can perform efficient coding even when external stimuli vary over multiple time scales. Together, these results suggest that key properties of biological neural networks may be accounted for by efficient coding.

Electrophysiological recordings during ketamine anesthesia have revealed a slow alternating pattern of high- and low-frequency activity (a "gamma-burst" pattern) that develops along with the onset of general anesthesia. We examine the role of NMDA receptor antagonism in generating the gamma-burst pattern and the link between gamma-bursts and dissociative anesthesia by comparing the effects of ketamine with those of the highly selective NMDA receptor antagonist CGS 19755 on multi-site intracranial electrophysiology and behavior in rhesus macaques. The data show NMDA antagonism alone drives gamma-burst activity, and that it can do so without causing anesthesia. This underscores the involvement of mechanisms other than NMDA antagonism in the anesthetic effects of ketamine.

Blastocystis , an obligate host-associated protist, is the most common microbial eukaryote in the human gut and is widely distributed across vertebrate hosts. The evolutionary transition of Blastocystis from its free-living stramenopile ancestors to a radiation of host-associated organisms is poorly understood. To explore this, we cultured and sequenced eight strains representing the significant phylogenetic diversity of the genus using long-read, short-read, and Hi-C DNA sequencing, alongside gene annotation and RNA sequencing. Comparative genomic analyses revealed significant variation in gene content and genome structure across Blastocystis. Notably, three strains from herbivorous tortoises, phylogenetically distant from human subtypes, have markedly larger genomes with longer introns and intergenic regions, and retain canonical stop codons absent in the human-associated strains. Despite these genetic differences, all eight isolates exhibit gene losses linked to the reduced cellular complexity of Blastocystis, including losses of cilia and flagella genes, microtubule motor genes, and signal transduction genes. Isolates from herbivorous tortoises contained higher numbers of plant carbohydrate-metabolizing enzymes, suggesting that like gut bacteria, these protists ferment plant material in the host gut. We find evidence that some of these carbohydrate-metabolizing enzymes were horizontally acquired from bacteria, indicating that horizontal gene transfer is an ongoing process in Blastocystis that has contributed to host-related adaptation. Together, these results highlight substantial genetic and metabolic diversity within the Blastocystis genus, indicating different lineages of Blastocystis have varied ecological roles in the host gut.

The expression of genomically-encoded information is not error-free. Transcript-error rates are dramatically higher than DNA-level mutation rates, and despite their transient nature, the steady-state load of such errors must impose some burden on cellular performance. However, a broad perspective on the degree to which transcript-error rates are constrained by natural selection and diverge among lineages remains to be developed. Here, we present a genome-wide analysis of transcript-error rates across the Tree of Life using a modified rolling-circle sequencing method, revealing that the range in error rates is remarkably narrow across diverse species. Transcript errors tend to be randomly distributed, with little evidence supporting local control of error rates associated with gene-expression levels. A majority of transcript errors result in missense errors if translated, and as with a fraction of nonsense transcript errors, these are underrepresented relative to random expectations, suggesting the existence of mechanisms for purging some such errors. To quantitatively understand how natural selection and random genetic drift might shape transcript-error rates across species, we present a model based on cell biology and population genetics, incorporating information on cell volume, proteome size, average degree of exposure of individual errors, and effective population size. However, while this model provides a framework for understanding the evolution of this highly conserved trait, as currently structured it explains only 20% of the variation in the data, suggesting a need for further theoretical work in this area.

Vectorization of teaching signals is a key element of virtually all modern machine learning algorithms, including backpropagation, target propagation and reinforcement learning. Vectorization allows a scalable and computationally efficient solution to the credit assignment problem by tailoring instructive signals to individual neurons. Recent theoretical models have suggested that neural circuits could implement single-phase vectorized learning at the cellular level by processing feedforward and feedback information streams in separate dendritic compartments^1-5. This presents a compelling, but untested, hypothesis for how cortical circuits could solve credit assignment in the brain. We leveraged a neurofeedback brain-computer interface (BCI) task with an experimenter-defined reward function to test for vectorized instructive signals in dendrites. We trained mice to modulate the activity of two spatially intermingled populations (4 or 5 neurons each) of layer 5 pyramidal neurons in the retrosplenial cortex to rotate a visual grating towards a target orientation while we recorded GCaMP activity from somas and corresponding distal apical dendrites. We observed that the relative magnitudes of somatic versus dendritic signals could be predicted using the activity of the surrounding network and contained information about task-related variables that could serve as instructive signals, including reward and error. The signs of these putative teaching signals both depended on the causal role of individual neurons in the task and predicted changes in overall activity over the course of learning. Furthermore, targeted optogenetic perturbation of these signals disrupted learning. These results provide the first biological evidence of a vectorized instructive signal in the brain, implemented via semi-independent computation in cortical dendrites, unveiling a potential mechanism for solving credit assignment in the brain.