Taube Koret Center

SUMMARYModification by ubiquitination governs the half-lives of thousands of proteins that are fated for elimination by either the proteasome or autophagy pathways, depending on the intricate architectures of ubiquitin modification. This system mediates quality control for individual proteins, protein complexes, and organelles, as well as myriad purely regulatory functions. Here we provide a comprehensive survey of the ubiquitin-proteasome system (UPS), the scope of which is at present poorly defined. The UPS, with the inclusion of pathways involving ubiquitin-like modifiers, comprises in our estimate over 1400 distinct proteins in humans, a vast set of activities whose collective impact on the biology of the cell is pervasive. The UPS is an integral component of the proteostasis network (PN), the remainder of which we have also surveyed in recent studies. With the addition of molecular chaperones, proteins from autophagy-lysosome pathway, and related activities, the PN includes in total over 3100 components by our estimates. Comprehensive and systematic definition of these pathways should support a range of ongoing investigations in the areas of genomics, proteomics, biochemistry, cell biology, and disease research.

The condition of having a healthy, functional proteome is known as protein homeostasis, or proteostasis. Establishing and maintaining proteostasis is the province of the proteostasis network, approximately 2,700 components that regulate protein synthesis, folding, localization, and degradation. The proteostasis network is a fundamental entity in biology that is essential for cellular health and has direct relevance to many diseases of protein conformation. However, it is not well defined or annotated, which hinders its functional characterization in health and disease. In this series of manuscripts, we aim to operationally define the human proteostasis network by providing a comprehensive, annotated list of its components. We provided in a previous manuscript a list of chaperones and folding enzymes as well as the components that make up the machineries for protein synthesis, protein trafficking into and out of organelles, and organelle-specific degradation pathways. Here, we provide a curated list of 838 unique high-confidence components of the autophagy-lysosome pathway, one of the two major protein degradation systems in human cells.

Numerous assays have been developed to monitor different stages or components of autophagy. However, relatively few methods exist for quantifying overall flow through the autophagy process, known as autophagic flux. Most commonly, autophagic flux is measured using a metabolic pulse-chase (MPC) assay, which labels a subset of proteins (“pulse”) and then measures levels of these proteins at regular intervals (“chase”) to estimate the mean half-life of proteins cleared by autophagy. In this chapter, we describe an alternative, imaging-based method for measuring autophagic flux, called optical pulse labeling (OPL). OPL offers a number of advantages over the MPC flux assay, namely (1) the ability to calculate protein half-lives in single cells, which allows analysis of subpopulations within a heterogeneous sample, and (2) the ability to multiplex with other assays and create extremely rich datasets. This chapter provides an overview of the advantages and limitations of OPL, and a detailed protocol for carrying out OPL in primary rodent neurons.

BackgroundLarge image datasets acquired on automated microscopes typically have some fraction of low quality, out-of-focus images, despite the use of hardware autofocus systems. Identification of these images using automated image analysis with high accuracy is important for obtaining a clean, unbiased image dataset. Complicating this task is the fact that image focus quality is only well-defined in foreground regions of images, and as a result, most previous approaches only enable a computation of the relative difference in quality between two or more images, rather than an absolute measure of quality.ResultsWe present a deep neural network model capable of predicting an absolute measure of image focus on a single image in isolation, without any user-specified parameters. The model operates at the image-patch level, and also outputs a measure of prediction certainty, enabling interpretable predictions. The model was trained on only 384 in-focus Hoechst (nuclei) stain images of U2OS cells, which were synthetically defocused to one of 11 absolute defocus levels during training. The trained model can generalize on previously unseen real Hoechst stain images, identifying the absolute image focus to within one defocus level (approximately 3 pixel blur diameter difference) with 95% accuracy. On a simpler binary in/out-of-focus classification task, the trained model outperforms previous approaches on both Hoechst and Phalloidin (actin) stain images (F-scores of 0.89 and 0.86, respectively over 0.84 and 0.83), despite only having been presented Hoechst stain images during training. Lastly, we observe qualitatively that the model generalizes to two additional stains, Hoechst and Tubulin, of an unseen cell type (Human MCF-7) acquired on a different instrument.ConclusionsOur deep neural network enables classification of out-of-focus microscope images with both higher accuracy and greater precision than previous approaches via interpretable patch-level focus and certainty predictions. The use of synthetically defocused images precludes the need for a manually annotated training dataset. The model also generalizes to different image and cell types. The framework for model training and image prediction is available as a free software library and the pre-trained model is available for immediate use in Fiji (ImageJ) and CellProfiler.

The misfolding of intrinsically disordered proteins such as α-synuclein, tau and the Aβ peptide has been associated with many highly debilitating neurodegenerative syndromes including Parkinson’s and Alzheimer’s diseases. Therapeutic targeting of the monomeric state of such intrinsically disordered proteins by small molecules has, however, been a major challenge because of their heterogeneous conformational properties. We show here that a combination of computational and experimental techniques has led to the identification of a drug-like phenyl-sulfonamide compound (ELN484228), that targets α-synuclein, a key protein in Parkinson’s disease. We found that this compound has substantial biological activity in cellular models of α-synuclein-mediated dysfunction, including rescue of α-synuclein-induced disruption of vesicle trafficking and dopaminergic neuronal loss and neurite retraction most likely by reducing the amount of α-synuclein targeted to sites of vesicle mobilization such as the synapse in neurons or the site of bead engulfment in microglial cells. These results indicate that targeting α-synuclein by small molecules represents a promising approach to the development of therapeutic treatments of Parkinson’s disease and related conditions.

We investigated the viability of psychometrically robust executive function measures as markers for premanifest Huntington's disease (HD). Fifteen premanifest HD subjects and 42 controls were compared on the NIH EXAMINER executive function battery. This battery yields an overall executive composite score, plus working memory, cognitive control, and fluency scores that are measured on psychometrically matched scales. The scores were correlated with two disease markers, disease burden and striatal volumes, in the premanifest HD subjects. The premanifest HD subjects scored significantly lower on the working memory score. The executive composite positively correlated with striatal volumes, and the working memory score negatively correlated with disease burden. The cognitive control and fluency scores did not differ between the groups or correlate significantly with the disease markers. The NIH EXAMINER executive composite and working memory scores are sensitive markers of cognitive dysfunction, striatal volume, and disease burden in premanifest HD.

Misfolded proteins have been implicated in most of the major neurodegenerative diseases, and identifying drugs and pathways that protect neurons from the toxicity of misfolded proteins is of paramount importance. We invented a form of automated imaging and analysis called robotic microscopy that is well suited to the study of neurodegeneration. It enables the monitoring of large cohorts of individual neurons over their lifetimes as they undergo neurodegeneration. With automated analysis, multiple endpoints in neurons can be measured, including survival. Statistical approaches, typically reserved for engineering and clinical medicine, can be applied to these data in an unbiased fashion to discover whether factors contribute positively or negatively to neuronal fate and to quantify the importance of their contribution. Ultimately, multivariate dynamic models can be constructed from these data, which can provide a systems-level understanding of the neurodegenerative disease process and guide the rationale for the development of therapies.

Peripheral immune cells and brain microglia exhibit an activated phenotype in premanifest Huntington's disease (HD) patients that persists chronically and correlates with clinical measures of neurodegeneration. However, whether activation of the immune system contributes to neurodegeneration in HD, or is a consequence thereof, remains unclear. Signaling through cannabinoid receptor 2 (CB(2)) dampens immune activation. Here, we show that the genetic deletion of CB(2) receptors in a slowly progressing HD mouse model accelerates the onset of motor deficits and increases their severity. Treatment of mice with a CB(2) receptor agonist extends life span and suppresses motor deficits, synapse loss, and CNS inflammation, while a peripherally restricted CB(2) receptor antagonist blocks these effects. CB(2) receptors regulate blood interleukin-6 (IL-6) levels, and IL-6 neutralizing antibodies partially rescue motor deficits and weight loss in HD mice. These findings support a causal link between CB(2) receptor signaling in peripheral immune cells and the onset and severity of neurodegeneration in HD, and they provide a novel therapeutic approach to treat HD.