Analysis of sheep α-synuclein provides a molecular strategy for the reduction of fibrillation

The ovine Type II Gaucher disease model recapitulates aspects of human brain disease

Acute neuronopathic (type II) Gaucher disease (GD) is a devastating, untreatable neurological disorder resulting from mutations in the glucocerebrosidase gene (GBA1), with subsequent accumulation of glucosylceramide and glucosylsphingosine. Patients experience progressive decline in neurological function, with onset typically within the first three-to-six months of life and premature death before two years. Mice and drosophila with GD have been described, however little is known about the brain pathology observed in the naturally occurring ovine model of GD. We have characterised pathological changes in GD lamb brain and compared the histological findings to those in GD patient post-mortem tissue, to determine the validity of the sheep as a model of this disease. Five GD and five age-matched unaffected lamb brains were examined. We observed significant expansion of the endo/lysosomal system in GD lamb cingulate gyrus however TPP1 and cathepsin D levels were unchanged or reduced. H&E staining revealed neurons with shrunken, hypereosinophilic cytoplasm and hyperchromatic or pyknotic nuclei (red neurons) that were also shrunken and deeply Nissl stain positive. Amoeboid microglia were noted throughout GD brain. Spheroidal inclusions reactive for TOMM20, ubiquitin and most strikingly, p-Tau were observed in many brain regions in GD lamb brain, potentially indicating disturbed axonal trafficking. Our findings suggest that the ovine model of GD exhibits similar pathological changes to human, mouse, and drosophila type II GD brain, and represents a model suitable for evaluating therapeutic intervention, particularly in utero-targeted approaches.

Advances in the Prediction of Protein Aggregation Propensity

Background:

Protein aggregation into β-sheet-enriched insoluble assemblies is being found to be associated with an increasing number of debilitating human pathologies, such as Alzheimer’s disease or type 2 diabetes, but also with premature aging. Furthermore, protein aggregation represents a major bottleneck in the production and marketing of proteinbased therapeutics. Thus, the development of methods to accurately forecast the aggregation propensity of a certain protein is of much value.

Methods/Results:

A myriad of in vitro and in vivo aggregation studies have shown that the aggregation propensity of a certain polypeptide sequence is highly dependent on its intrinsic properties and, in most cases, driven by specific short regions of high aggregation propensity. These observations have fostered the development of a first generation of algorithms aimed to predict protein aggregation propensities from the protein sequence. A second generation of programs able to map protein aggregation on protein structures is emerging. Herein, we review the most representative online accessible predictive tools, emphasizing their main distinctive features and the range of applications.

Conclusion:

In this review, we describe representative biocomputational approaches to evaluate the aggregation properties of protein sequences and structures, while illustrating how they can become very useful tools to target protein aggregation in biomedicine and biotechnology.