Rescuing defective vesicular trafficking protects against alpha-synuclein toxicity in cellular and animal models of Parkinson's disease

Studies in yeast are providing critical insights into the mechanisms of neurodegeneration in Parkinson's disease (PD). A recent study shows that disruption of vesicular trafficking between the endoplasmic reticulum (ER) and the Golgi, caused by the overexpression and/or aggregation of alpha-synuclein, is linked to degeneration of dopamine neurons. Overexpression of proteins that are known to enhance ER-to-Golgi transport rescue defective trafficking in yeast, worm, fly, and cellular models of PD

Modulation of receptor cycling by neuron-enriched endosomal protein of 21 kD

Although correct cycling of neuronal membrane proteins is essential for neurite outgrowth and synaptic plasticity, neuron-specific proteins of the implicated endosomes have not been characterized. Here we show that a previously cloned, developmentally regulated, neuronal protein of unknown function binds to syntaxin 13. We propose to name this protein neuron-enriched endosomal protein of 21 kD (NEEP21), because it is colocalized with transferrin receptors, internalized transferrin (Tf), and Rab4. In PC12 cells, NEEP21 overexpression accelerates Tf internalization and recycling, whereas its down-regulation strongly delays Tf recycling. In primary neurons, NEEP21 is localized to the somatodendritic compartment, and, upon N-methyl-d-aspartate (NMDA) stimulation, the alpha-amino-3-hydroxy-5-methyl-4-isoxazolepropionate receptor subunit GluR2 is internalized into NEEP21-positive endosomes. NEEP21 down-regulation retards recycling of GluR1 to the cell surface after NMDA stimulation of hippocampal neurons. In summary, NEEP21 is a neuronal protein that is localized to the early endosomal pathway and is necessary for correct receptor recycling in neurons

pyC2^2Ray: A flexible and GPU-accelerated Radiative Transfer Framework for Simulating the Cosmic Epoch of Reionization

Detailed modelling of the evolution of neutral hydrogen in the intergalactic medium during the Epoch of Reionization, $5 \leq z \leq 20$, is critical in interpreting the cosmological signals from current and upcoming 21-cm experiments such as Low-Frequency Array (LOFAR) and the Square Kilometre Array (SKA). Numerical radiative transfer codes offer the most physically motivated approach for simulating the reionization process. However, they are computationally expensive as they must encompass enormous cosmological volumes while accurately capturing astrophysical processes occurring at small scales ($\lesssim\rm Mpc$). Here, we present pyC$^2$Ray, an updated version of the massively parallel ray-tracing and chemistry code, C$^2$Ray, which has been extensively employed in reionization simulations. The most time-consuming part of the code is calculating the hydrogen column density along the path of the ionizing photons. Here, we present the Accelerated Short-characteristics Octhaedral RAytracing (ASORA) method, a ray-tracing algorithm specifically designed to run on graphical processing units (GPUs). We include a modern Python interface, allowing easy and customized use of the code without compromising computational efficiency. We test pyC$^2$Ray on a series of standard ray-tracing tests and a complete cosmological simulation with volume size $(349\,\rm Mpc)^3$, mesh size of $250^3$ and approximately $10^6$ sources. Compared to the original code, pyC$^2$Ray achieves the same results with negligible fractional differences, $\sim 10^{-5}$, and a speedup factor of two orders of magnitude. Benchmark analysis shows that ASORA takes a few nanoseconds per source per voxel and scales linearly for an increasing number of sources and voxels within the ray-tracing radii.Comment: 16 pages, 13 figure

Cell lines and clearing approaches : a single-cell level 3D light-sheet fluorescence microscopy dataset of multicellular spheroids

Nowadays, three dimensional (3D) cell cultures are widely used in the biological laboratories and several optical clearing approaches have been proposed to visualize individual cells in the deepest layers of cancer multicellular spheroids. However, defining the most appropriate clearing approach for the different cell lines is an open issue due to the lack of a gold standard quantitative metric. In this article, we describe and share a single-cell resolution 3D image dataset of human carcinoma spheroids imaged using a light-sheet fluorescence microscope. The dataset contains 90 multicellular cancer spheroids derived from 3 cell lines (i.e. T-47D, 5-8F, and Huh-7D12) and cleared with 5 different protocols, precisely Clear(T) , Clear(T2) , CUBIC, ScaleA2, and Sucrose. To evaluate image quality and light penetration depth of the cleared 3D samples, all the spheroids have been imaged under the same experimental conditions, labelling the nuclei with the DRAQ(5) stain and using a Leica SP8 Digital LightSheet microscope. The clearing quality of this dataset was annotated by 10 independent experts and thus allows microscopy users to qualitatively compare the effects of different optical clearing protocols on different cell lines. It is also an optimal testbed to quantitatively assess different com putational metrics evaluating the image quality in the deepest layers of the spheroids. (C) 2021 The Author(s). Published by Elsevier Inc.Peer reviewe

A quantitative metric for the comparative evaluation of optical clearing protocols for 3D multicellular spheroids

3D multicellular spheroids quickly emerged as in vitro models because they represent the in vivo tumor environment better than standard 2D cell cultures. However, with current microscopy technologies, it is difficult to visualize individual cells in the deeper layers of 3D samples mainly because of limited light penetration and scattering. To overcome this problem several optical clearing methods have been proposed but defining the most appropriate clearing approach is an open issue due to the lack of a gold standard metric. Here, we propose a guideline for 3D light microscopy imaging to achieve single-cell resolution. The guideline includes a validation experiment focusing on five optical clearing protocols. We review and compare seven quality metrics which quantitatively characterize the imaging quality of spheroids. As a test environment, we have created and shared a large 3D dataset including approximately hundred fluorescently stained and optically cleared spheroids. Based on the results we introduce the use of a novel quality metric as a promising method to serve as a gold standard, applicable to compare optical clearing protocols, and decide on the most suitable one for a particular experiment. (C) 2021 The Authors. Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology.Peer reviewe

A quantitative metric for the comparative evaluation of optical clearing protocols for 3D multicellular spheroids

3D multicellular spheroids quickly emerged as in vitro models because they represent the in vivo tumor environment better than standard 2D cell cultures. However, with current microscopy technologies, it is difficult to visualize individual cells in the deeper layers of 3D samples mainly because of limited light penetration and scattering. To overcome this problem several optical clearing methods have been proposed but defining the most appropriate clearing approach is an open issue due to the lack of a gold standard metric. Here, we propose a guideline for 3D light microscopy imaging to achieve single-cell resolution. The guideline includes a validation experiment focusing on five optical clearing protocols. We review and compare seven quality metrics which quantitatively characterize the imaging quality of spheroids. As a test environment, we have created and shared a large 3D dataset including approximately hundred fluorescently stained and optically cleared spheroids. Based on the results we introduce the use of a novel quality metric as a promising method to serve as a gold standard, applicable to compare optical clearing protocols, and decide on the most suitable one for a particular experiment

Iron-regulatory proteins: molecular biology and pathophysiological implications

Iron is required for key cellular functions, and there is a strong link between iron metabolism and important metabolic processes, such as cell growth, apoptosis and inflammation. Diseases that are directly or indirectly related to iron metabolism represent major health problems. Iron-regulatory proteins (IRPs) 1 and 2 are key controllers of vertebrate iron metabolism and post-transcriptionally regulate expression of the major iron homeostasis genes. Here we discuss how dysregulation of the IRP system can result from both iron-related and unrelated effectors and explain how this can have important pathological consequences in several human disorders

Design and Validation of a Tool for Neurite Tracing and Analysis in Fluorescence Microscopy Images

Background: For the investigation of the molecular mechanisms involved in neurite outgrowth and differentiation, accurate and reproducible segmentation and quantification of neuronal processes are a prerequisite. To facilitate this task, we developed a semiautomatic neurite tracing technique. This article describes the design and validation of the technique. Methods: The technique was compared to fully manual delineation. Four observers repeatedly traced selected neurites in 20 fluorescence microscopy images of cells in culture, using both methods. Accuracy and reproducibility were determined by comparing the tracings to high-resolution reference tracings, using two error measures. Labor intensiveness was measured in numbers of mouse clicks required. The significance of the results was determined by a Student t-test and by analysis of variance. Results: Both methods slightly underestimated the true neurite length, but the differences were not unanimously significant. The average deviation from the true neurite centerline was a factor 2.6 smaller with the developed technique compared to fully manual tracing. Intraobserver variability in the respective measures was reduced by a factor 6.0 and 23.2. Interobserver variability was reduced by a factor 2.4 and 8.8, respectively, and labor intensiveness by a factor 3.3. Conclusions: Providing similar accuracy in measuring neurite length, significantly improved accuracy in neurite centerline extraction, and significantly improved reproducibility and reduced labor intensiveness, the developed technique may replace fully manual tracing methods