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Chloride permeation in lysosomes There has been much interest in the CLC family of membrane proteins since it has become apparent that some members are chlorine ion conducting ion channels whilst others are antiporters for chlorine and hydrogen ions. An antiporter is a membrane protein that is involved in active transport of two or more different ligands. In this paper, Graves et al . show that ClC-7 is a Cl − /H + antiporter in lysosomal membranes, whose activity maintains the correct membrane voltage during acidification of the organelle. Interestingly, this work also reinforces the idea that plasma membrane CLCs are dedicated Cl − channels, whereas 'intracellular' CLCs are antiporters. This represents direct evidence that a CLC protein is responsible for the long-hypothesized chloride permeability of lysosomal membranes. This paper shows that ClC-7 is a Cl − /H + antiporter in lysosomal membranes, the activity of which maintains the correct membrane voltage during acidification of the organelle. This work reinforces the idea that plasma membrane CLCs are Cl − channels whereas 'intracellular' CLCs are antiporters. Lysosomes are the stomachs of the cell—terminal organelles on the endocytic pathway where internalized macromolecules are degraded. Containing a wide range of hydrolytic enzymes, lysosomes depend on maintaining acidic luminal pH values for efficient function. Although acidification is mediated by a V-type proton ATPase, a parallel anion pathway is essential to allow bulk proton transport 1 , 2 . The molecular identity of this anion transporter remains unknown. Recent results of knockout experiments raise the possibility that ClC-7, a member of the CLC family of anion channels and transporters, is a contributor to this pathway in an osteoclast lysosome-like compartment, with loss of ClC-7 function causing osteopetrosis 3 . Several mammalian members of the CLC family have been characterized in detail; some (including ClC-0, ClC-1 and ClC-2) function as Cl - -conducting ion channels 4 , whereas others act as Cl - /H + antiporters (ClC-4 and ClC-5) 5 , 6 . However, previous attempts at heterologous expression of ClC-7 have failed to yield evidence of functional protein, so it is unclear whether ClC-7 has an important function in lysosomal biology, and also whether this protein functions as a Cl - channel, a Cl - /H + antiporter, or as something else entirely. Here we directly demonstrate an anion transport pathway in lysosomes that has the defining characteristics of a CLC Cl - /H + antiporter and show that this transporter is the predominant route for Cl - through the lysosomal membrane. Furthermore, knockdown of ClC-7 expression by short interfering RNA can essentially ablate this lysosomal Cl - /H + antiport activity and can strongly diminish the ability of lysosomes to acidify in vivo , demonstrating that ClC-7 is a Cl - /H + antiporter, that it constitutes the major Cl - permeability of lysosomes, and that it is important in lysosomal acidification.

Mammalian cerebral cortex is accepted as being critical for voluntary motor control, but what functions depend on cortex is still unclear. Here we used rapid, reversible optogenetic inhibition to test the role of cortex during a head-fixed task in which mice reach, grab, and eat a food pellet. Sudden cortical inhibition blocked initiation or froze execution of this skilled prehension behavior, but left untrained forelimb movements unaffected. Unexpectedly, kinematically normal prehension occurred immediately after cortical inhibition, even during rest periods lacking cue and pellet. This ‘rebound’ prehension was only evoked in trained and food-deprived animals, suggesting that a motivation-gated motor engram sufficient to evoke prehension is activated at inhibition’s end. These results demonstrate the necessity and sufficiency of cortical activity for enacting a learned skill. Many of the movements that humans and other animals make every day are deceptively complex and only appear easy because of extensive practice. For example, picking up an object involves several steps that must be precisely controlled, including reaching towards the item and holding it using the right amount of pressure to not crush it or drop it. Part of the brain called the motor cortex is thought to be important for learning and controlling these skilled movements, but its exact role in these processes is not clear. A technique called optogenetics allows the roles of individual parts of the brain to be studied by rapidly altering their activity, whilst minimizing the likelihood that the brain will compensate for these changes. By genetically modifying animals to produce light-sensitive channel proteins in certain brain cells, the activity of particular regions of the brain can be controlled by shining light onto them. Guo et al. have now used optogenetics to control the motor cortex as the mice performed a task they had been trained to do – reaching for and picking up a food pellet. Suddenly shutting down the motor cortex at the start of a trial prevented the mice from starting the task, and shut down part way through the task caused the front limbs of the mice to freeze in midair. However, only the learned, skilled task was frozen by motor cortex shutdown; mice could still move their limbs normally if the motor cortex was instead shut down during routine movements. When the cortex was reactivated, the mice instantly resumed trying to pick up the food pellet. Unexpectedly, even during rest periods when there was no food pellet and the mice were just waiting for the experiment to begin, turning the motor cortex off and then back on again suddenly caused the mice to perform the complete grabbing motion. This implies that the cortical activity evoked at the end of inactivation acts to trigger the full movement sequence. This was particularly likely to occur if the animal had been deprived of food before the test or was particularly well trained, but did not depend on the position of the limb. Overall, Guo et al.’s work opens the question of how the instructions that describe the learned movement are encoded within the motor cortex and its downstream networks. Future studies could also investigate how learning a set of movements affects the structure of cortical neurons and their connections, thus suggesting how these memories are stored.

To control reaching, the nervous system must generate large changes in muscle activation to drive the limb toward the target, and must also make smaller adjustments for precise and accurate behavior. Motor cortex controls the arm through projections to diverse targets across the central nervous system, but it has been challenging to identify the roles of cortical projections to specific targets. Here, we selectively disrupt cortico-cerebellar communication in the mouse by optogenetically stimulating the pontine nuclei in a cued reaching task. This perturbation did not typically block movement initiation, but degraded the precision, accuracy, duration, or success rate of the movement. Correspondingly, cerebellar and cortical activity during movement were largely preserved, but differences in hand velocity between control and stimulation conditions predicted from neural activity were correlated with observed velocity differences. These results suggest that while the total output of motor cortex drives reaching, the cortico-cerebellar loop makes small adjustments that contribute to the successful execution of this dexterous movement.

Elucidating how synaptic molecules such as AMPA receptors mediate neuronal communication and tracking their dynamic expression during behavior is crucial to understand cognition and disease, but current technological barriers preclude large-scale exploration of molecular dynamics in vivo. We have developed a suite of innovative methodologies that break through these barriers: a new knockin mouse line with fluorescently tagged endogenous AMPA receptors, two-photon imaging of hundreds of thousands of labeled synapses in behaving mice, and computer vision-based automatic synapse detection. Using these tools, we can longitudinally track how the strength of populations of synapses changes during behavior. We used this approach to generate an unprecedentedly detailed spatiotemporal map of synapses undergoing changes in strength following sensory experience. More generally, these tools can be used as an optical probe capable of measuring functional synapse strength across entire brain areas during any behavioral paradigm, describing complex system-wide changes with molecular precision.

Regulation of AMPA receptor (AMPAR) expression is central to synaptic plasticity and brain function, but how these changes occur in vivo remains elusive. Here, we developed a method to longitudinally monitor the expression of synaptic AMPARs across multiple cortical layers in awake mice using two-photon imaging. We observed that baseline AMPAR expression in individual spines is highly dynamic with more dynamics in primary visual cortex (V1) layer 2/3 (L2/3) neurons than V1 L5 neurons. Visual deprivation through binocular enucleation induces a synapse-specific and depth-dependent change of synaptic AMPARs in V1 L2/3 neurons, wherein deep synapses are potentiated more than superficial synapses. The increase is specific to L2/3 neurons and absent on apical dendrites of L5 neurons, and is dependent on expression of the AMPAR-binding protein GRIP1. Our study demonstrates that specific neuronal connections, across cortical layers and even within individual neurons, respond uniquely to changes in sensory experience.

Learning is thought to involve changes in glutamate receptors at synapses, submicron structures that mediate communication between neurons in the central nervous system. Due to their small size and high density, synapses are difficult to resolve in vivo, limiting our ability to directly relate receptor dynamics to animal behavior. Here we developed a combination of computational and biological methods to overcome these challenges. First, we trained a deep-learning image-restoration algorithm that combines the advantages of ex vivo super-resolution and in vivo imaging modalities to overcome limitations specific to each optical system. When applied to in vivo images from transgenic mice expressing fluorescently labeled glutamate receptors, this restoration algorithm super-resolved synapses, enabling the tracking of behavior-associated synaptic plasticity with high spatial resolution. This method demonstrates the capabilities of image enhancement to learn from ex vivo data and imaging techniques to improve in vivo imaging resolution. XTC is a supervised deep-learning-based image-restoration approach that is trained with images from different modalities and applied to an in vivo modality with no ground truth. XTC’s capabilities are demonstrated in synapse tracking in the mouse brain.

Abstract Primary age-related tauopathy (PART) is characterized by aggregation of tau in the mesial temporal lobe in older individuals. High pathologic tau stage (Braak stage) or a high burden of hippocampal tau pathology has been associated with cognitive impairment in PART. However, the potential underlying mechanisms are not well understood. Cognitive impairment in many neurodegenerative diseases correlates with synaptic loss, raising the question of whether synaptic loss also occurs in PART. To address this, we investigated synaptic changes associated with tau Braak stage and high tau pathology burden in PART using synaptophysin and phospho-tau immunofluorescence. We compared 12 cases of definite PART with 6 controls and 6 Alzheimer disease cases. In this study, the hippocampal CA2 region showed loss of synaptophysin puncta and intensity in cases of PART with either a high stage (Braak IV) or a high burden of neuritic tau pathology. There was also loss of synaptophysin intensity in CA3 associated with a high stage or high burden of tau pathology. Loss of synaptophysin was present in Alzheimer disease, but the pattern appeared distinct. These novel findings suggest the presence of synaptic loss associated with either a high hippocampal tau burden or a Braak stage IV in PART.

The growing channel count of silicon probes has substantially increased the number of neurons recorded in electrophysiology (ephys) experiments, rendering traditional manual spike sorting impractical. Instead, modern ephys recordings are processed with automated methods that use waveform template matching to isolate putative single neurons. While scalable, automated methods are subject to assumptions that often fail to account for biophysical changes in action potential waveforms, leading to systematic errors. Consequently, manual curation of these errors, which is both time-consuming and lacks reproducibility, remains necessary. To improve efficiency and reproducibility in the spike-sorting pipeline, we introduce here the Spike-sorting Lapse Amelioration System (SLAy), an algorithm that automatically merges oversplit spike clusters. SLAy employs two novel metrics: (1) a waveform similarity metric that uses a neural network to obtain spatially informed, time-shift invariant low-dimensional waveform representations, and (2) a cross-correlogram significance metric based on the earth-mover's distance between the observed and null cross-correlograms. On a diverse set of datasets with realistic simulated oversplitting, SLAy achieves high recall and near-perfect precision in identifying ground truth merges. We also demonstrate that SLAy achieves ~ 85% with human curators across a diverse set of animal models, brain regions, and probe geometries. To illustrate the impact of spike sorting errors on downstream analyses, we develop a new burst-detection algorithm and show that SLAy fixes spike sorting errors that preclude the accurate detection of bursts in neural data. SLAy leverages GPU parallelization and multithreading for computational efficiency, and is compatible with Phy and NeuroData Without Borders, making it a practical and flexible solution for large-scale ephys data analysis.

Synapses are the fundamental unit of neural connectivity. They exhibit dynamic functional and structural changes that enable the brain to learn, adapt, and form memories. Recent advances in endogenous protein fluorescent labeling offer an opportunity to image synaptic strength and thus study the mechanisms underlying adaptive neural computation in living mice. Studying synaptic dynamics requires tracking individual signals of small, densely packed synapses over days while they change in size, position, and intensity between imaging sessions, and may even appear/disappear entirely. Tracking >100,000 dynamic, submicrometer particles is difficult even for state-of-the-art algorithms. Moreover, most algorithms rely on an isotropic uncertainty ball, assigning equal weight to the lateral plane (XY) and to the noisier axial dimension (Z), leading to poorer performance. To address these challenges and accurately track synapses , we developed SynTrack. We formulated SynTrack as a Maximum estimation problem under the anisotropic uncertainty ball, along with a fully temporally connected spatio-temporal graph to overcome long-term occlusions. SynTrack achieves a mean track length of 0.51 m with a Multiple Object Tracking Accuracy (MOTA) score of 88.8%, on par with MOTA scores of expert annotators but with massively increased speed and scalability. Over two weeks, we successfully track 65,000 synapses in 5.6 out of 8 imaging sessions on average, with 20,000 synapses being tracked in at least seven sessions. We present SynTrack as a state-of-the-art algorithm capable of high-resolution and fidelity tracking of synapse dynamics in behaving mice with unprecedented detail.