Probing the effects of N-terminal acetylation on α-synuclein structure, aggregation and cytotoxicity.

Parkinson's disease is associated with the aberrant aggregation of α-synuclein within brain cells. Although the causes of this process are still unclear, post-translational modifications of α-synuclein are likely to play a modulatory role. Since α-synuclein is constitutively N-terminally acetylated, we previously investigated how this protein modification affects the aggregation behavior of the protein using a variety of methods in vitro and in cell systems. This chapter describes the production of N-terminally acetylated (NTA) α-synuclein, the preparation of different seeds of NTA α-synuclein for aggregation assays and the experimental methods for the kinetic analysis of the aggregation process of NTA α-synuclein. We also detail our protocol to evaluate the effects of preformed protofibrils of NTA α-synuclein in cell-based assays. These methods can be applied to study other post-translational modifications of α-synuclein, or adapted for the study of N-acetylation of other aggregation-prone proteins.

Sequence-based prediction of pH-dependent protein solubility using CamSol.

Solubility is a property of central importance for the use of proteins in research in molecular and cell biology and in applications in biotechnology and medicine. Since experimental methods for measuring protein solubility are material intensive and time consuming, computational methods have recently emerged to enable the rapid and inexpensive screening of solubility for large libraries of proteins, as it is routinely required in development pipelines. Here, we describe the development of one such method to include in the predictions the effect of the pH on solubility. We illustrate the resulting pH-dependent predictions on a variety of antibodies and other proteins to demonstrate that these predictions achieve an accuracy comparable with that of experimental methods. We make this method publicly available at https://www-cohsoftware.ch.cam.ac.uk/index.php/camsolph, as the version 3.0 of CamSol.

Effects of N-terminal Acetylation on the Aggregation of Disease-related α-synuclein Variants.

Mutations in the SNCA gene, which encodes the protein α-synuclein, have been linked with early onset Parkinson's disease. The exact nature of this association, however, is still poorly understood. To investigate this problem, we started from the observation that α-synuclein is constitutively N-terminally acetylated, a post-translational modification that alters the charge and structure of α-synuclein molecules and affects their interaction with lipid membranes, as well as their aggregation process. We thus studied five N-terminal acetylated familial variants (A30P, E46K, H50Q, G51D and A53T) of α-synuclein through a wide range of biophysical assays to probe the microscopic steps in their aggregation process and the structures of the resulting aggregates. Our results reveal a great complexity in the combined effects of the disease-related mutations with N-terminal acetylation on the aggregation of α-synuclein, which underscores the great sensitivity to even relatively small perturbations of the behaviour of this protein.

N-Terminal Acetylation of α-Synuclein Slows down Its Aggregation Process and Alters the Morphology of the Resulting Aggregates.

Parkinson's disease is associated with the aberrant aggregation of α-synuclein. Although the causes of this process are still unclear, post-translational modifications of α-synuclein are likely to play a modulatory role. Since α-synuclein is constitutively N-terminally acetylated, we investigated how this post-translational modification alters the aggregation behavior of this protein. By applying a three-pronged aggregation kinetics approach, we observed that N-terminal acetylation results in a reduced rate of lipid-induced aggregation and slows down both elongation and fibril-catalyzed aggregate proliferation. An analysis of the amyloid fibrils produced by the aggregation process revealed different morphologies for the acetylated and non-acetylated forms in both lipid-induced aggregation and seed-induced aggregation assays. In addition, we found that fibrils formed by acetylated α-synuclein exhibit a lower ß-sheet content. These findings indicate that N-terminal acetylation of α-synuclein alters its lipid-dependent aggregation behavior, reduces its rate of in vitro aggregation, and affects the structural properties of its fibrillar aggregates.

Modulation of the Interactions Between α-Synuclein and Lipid Membranes by Post-translational Modifications.

Parkinson's disease is characterised by the presence in brain tissue of aberrant inclusions known as Lewy bodies and Lewy neurites, which are deposits composed by α-synuclein and a variety of other cellular components, including in particular lipid membranes. The dysregulation of the balance between lipid homeostasis and α-synuclein homeostasis is therefore likely to be closely involved in the onset and progression of Parkinson's disease and related synucleinopathies. As our understanding of this balance is increasing, we describe recent advances in the characterisation of the role of post-translational modifications in modulating the interactions of α-synuclein with lipid membranes. We then discuss the impact of these advances on the development of novel diagnostic and therapeutic tools for synucleinopathies.

Evaluation of cerebrospinal fluid proteins as potential biomarkers for early stage Parkinson's disease diagnosis.

Cerebrospinal fluid (CSF) has often been used as the source of choice for biomarker discovery with the goal to support the diagnosis of neurodegenerative diseases. For this study, we selected 15 CSF protein markers which were identified in previously published clinical investigations and proposed as potential biomarkers for PD diagnosis. We aimed at investigating and confirming their suitability for early stage diagnosis of the disease. The current study was performed in a two-fold confirmatory approach. Firstly, the CSF protein markers were analysed in confirmatory cohort I comprising 80 controls and 80 early clinical PD patients. Through univariate analysis we found significant changes of six potential biomarkers (α-syn, DJ-1, Aß42, S100ß, p-Tau and t-Tau). In order to increase robustness of the observations for potential patient differentiation, we developed-based on a machine learning approach-an algorithm which enabled identifying a panel of markers which would improve clinical diagnosis. Based on that model, a panel comprised of α-syn, S100ß and UCHL1 were suggested as promising candidates. Secondly, we aimed at replicating our observations in an independent cohort (confirmatory cohort II) comprising 30 controls and 30 PD patients. The univariate analysis demonstrated Aß42 as the only reproducible potential biomarker. Taking into account both technical and clinical aspects, these observations suggest that the large majority of the investigated CSF proteins currently proposed as potential biomarkers lack robustness and reproducibility in supporting diagnosis in the early clinical stages of PD.

miRNA-based signatures in cerebrospinal fluid as potential diagnostic tools for early stage Parkinson's disease.

Parkinson's Disease is the second most common neurodegenerative disorder, affecting 1-2% of the elderly population. Its diagnosis is still based on the identification of motor symptoms when a considerable number of dopaminergic neurons are already lost. The development of translatable biomarkers for accurate diagnosis at the earliest stages of PD is of extreme interest. Several microRNAs have been associated with PD pathophysiology. Consequently, microRNAs are emerging as potential biomarkers, especially due to their presence in Cerebrospinal Fluid and peripheral circulation. This study employed small RNA sequencing, protein binding ligand assays and machine learning in a cross-sectional cohort comprising 40 early stage PD patients and 40 well-matched controls. We identified a panel comprising 5 microRNAs (Let-7f-5p, miR-27a-3p, miR-125a-5p, miR-151a-3p and miR-423-5p), with 90% sensitivity, 80% specificity and 82% area under the curve (AUC) for the differentiation of the cohorts. Moreover, we combined miRNA profiles with hallmark-proteins of PD and identified a panel (miR-10b-5p, miR-22-3p, miR-151a-3p and α-synuclein) reaching 97% sensitivity, 90% specificity and 96% AUC. We performed a gene ontology analysis for the genes targeted by the microRNAs present in each panel and showed the likely association of the models with pathways involved in PD pathogenesis.

Recent developments in circulating biomarkers in Parkinson's disease: the potential use of miRNAs in a clinical setting.

Parkinson's disease (PD) is the second most common neurodegenerative disorder, affecting 5% of the elderly population. PD diagnosis is still based on the identification of neuromotor symptoms although nonmotor manifestations emerge years prior to diagnosis. The discovery of biomarkers at the earliest stages of PD is of extreme interest. miRNAs have been considered potential biomarkers for neurodegenerative diseases, but only a limited number have been found to be PD related. This review focuses on the current findings in the field of circulating miRNAs in PD and the challenges surrounding clinical utility and validation. We briefly describe the more established circulating biomarkers in PD and provide a more thorough review of miRNAs differentially expressed in PD. We highlight their potential for being considered as biomarkers for diagnosis while emphasizing the challenges for adequate validation of the findings and how miRNAs can be envisioned in a clinical setting satisfying regulatory bodies.