Transport of the alpha subunit of the voltage gated Lâ type calcium channel through the sarcoplasmic reticulum occurs prior to localization to triads and requires the beta subunit but not Stac3 in skeletal muscles

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/138228/1/tra12502-sup-0001-EditorialProcess.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/138228/2/tra12502.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/138228/3/tra12502_am.pd

Automated four-dimensional long term imaging enables single cell tracking within organotypic brain slices to study neurodevelopment and degeneration.

Current approaches for dynamic profiling of single cells rely on dissociated cultures, which lack important biological features existing in tissues. Organotypic slice cultures preserve aspects of structural and synaptic organisation within the brain and are amenable to microscopy, but established techniques are not well adapted for high throughput or longitudinal single cell analysis. Here we developed a custom-built, automated confocal imaging platform, with improved organotypic slice culture and maintenance. The approach enables fully automated image acquisition and four-dimensional tracking of morphological changes within individual cells in organotypic cultures from rodent and human primary tissues for at least 3 weeks. To validate this system, we analysed neurons expressing a disease-associated version of huntingtin (HTT586Q138-EGFP), and observed that they displayed hallmarks of Huntington's disease and died sooner than controls. By facilitating longitudinal single-cell analyses of neuronal physiology, our system bridges scales necessary to attain statistical power to detect developmental and disease phenotypes

The arrival directions of the most energetic cosmic rays

In this Letter we examine the arrival directions of the most energetic cosmic rays (E > 2 * 10^19 eV) detected by several air shower experiments. We find that data taken by different air shower arrays show positive correlations, indicating a non--uniform arrival direction distribution. We also find that the events with energy $ > 4 * 10^19 eV exhibit a correlation with the general direction of the supergalactic plane, where a large number of potential sources is located. If confirmed by data from other experiments our results would support models for the extragalactic origin of the highest energy cosmic rays.Comment: 7 pages; 1 figure included; uuencoded, compressed PostScript file; final version, corrected in some points, accepted for publication in Phys.Rev.Let

Stac3 is a component of the excitation–contraction coupling machinery and mutated in Native American myopathy

Excitation-contraction coupling, the process that regulates contractions by skeletal muscles, transduces changes in membrane voltage by activating release of Ca2+ from internal stores to initiate muscle contraction. Defects in EC coupling are associated with muscle diseases. Here we identify Stac3 as a novel component of the EC coupling machinery. Using a zebrafish genetic screen, we generate a locomotor mutation that is mapped to stac3. We provide electrophysiological, Ca2+ imaging, immunocytochemical and biochemical evidence that Stac3 participates in excitation-contraction coupling in muscles. Furthermore, we reveal that a mutation in human STAC3 as the genetic basis of the debilitating Native American myopathy (NAM). Analysis of NAM stac3 in zebrafish shows that the NAM mutation decreases excitation-contraction coupling. These findings enhance our understanding of both excitation-contraction coupling and the pathology of myopathies

Cell death assays for neurodegenerative disease drug discovery

Introduction: Neurodegenerative diseases affect millions of people worldwide. Neurodegeneration is gradual over time, characterized by neuronal death that causes deterioration of cognitive or motor functions, ultimately leading to the patient's death. Currently, there are no treatments that effectively slow the progression of any neurodegenerative disease, but improved microscopy assays and models for neurodegeneration could lead the way to the discovery of disease-modifying therapeutics. Areas covered: Herein, the authors describe cell-based assays used to discover drugs with the potential to slow neurodegeneration, and their associated disease models. They focus on microscopy technologies that can be adapted to a high-throughput screening format that both detect cell death and monitor early signs of neurodegeneration and functional changes to identify drugs that the block early stages of neurodegeneration. Expert opinion: Many different phenotypes have been used in screens for the development of therapeutics towards neurodegenerative disease. The context of each phenotype in relation to neurodegeneration must be established to identify therapeutics likely to successfully target and treat disease. The use of improved models of neurodegeneration, statistical analyses, computational models, and improved markers of neuronal death will help in this pursuit and lead to better screening methods to identify therapeutic compounds against neurodegenerative disease

Fluorescently labeled nuclear morphology is highly informative of neurotoxicity

Neurotoxicity can be detected in live microscopy by morphological changes such as retraction of neurites, fragmentation, blebbing of the neuronal soma and ultimately the disappearance of fluorescently labeled neurons. However, quantification of these features is often difficult, low-throughput, and imprecise due to the overreliance on human curation. Recently, we showed that convolutional neural network (CNN) models can outperform human curators in the assessment of neuronal death from images of fluorescently labeled neurons, suggesting that there is information within the images that indicates toxicity but that is not apparent to the human eye. In particular, the CNN's decision strategy indicated that information within the nuclear region was essential for its superhuman performance. Here, we systematically tested this prediction by comparing images of fluorescent neuronal morphology from nuclear-localized fluorescent protein to those from freely diffused fluorescent protein for classifying neuronal death. We found that biomarker-optimized (BO-) CNNs could learn to classify neuronal death from fluorescent protein-localized nuclear morphology (mApple-NLS-CNN) alone, with super-human accuracy. Furthermore, leveraging methods from explainable artificial intelligence, we identified novel features within the nuclear-localized fluorescent protein signal that were indicative of neuronal death. Our findings suggest that the use of a nuclear morphology marker in live imaging combined with computational models such mApple-NLS-CNN can provide an optimal readout of neuronal death, a common result of neurotoxicity