The H50Q mutation induces a 10-fold decrease in the solubility of α-synuclein

CPAD, Curated Protein Aggregation Database: A Repository of Manually Curated Experimental Data on Protein and Peptide Aggregation

Accurate distinction between peptide sequences that can form amyloid-fibrils or amorphous β-aggregates, identification of potential aggregation prone regions in proteins, and prediction of change in aggregation rate of a protein upon mutation(s) are critical to research on protein misfolding diseases, such as Alzheimer’s and Parkinson’s, as well as biotechnological production of protein based therapeutics. We have developed a Curated Protein Aggregation Database (CPAD), which has collected results from experimental studies performed by scientific community aimed at understanding protein/peptide aggregation. CPAD contains more than 2300 experimentally observed aggregation rates upon mutations in known amyloidogenic proteins. Each entry includes numerical values for the following parameters: change in rate of aggregation as measured by fluorescence intensity or turbidity, name and source of the protein, Uniprot and Protein Data Bank codes, single point as well as multiple mutations, and literature citation. The data in CPAD has been supplemented with five different types of additional information: (i) Amyloid fibril forming hexa-peptides, (ii) Amorphous β-aggregating hexa-peptides, (iii) Amyloid fibril forming peptides of different lengths, (iv) Amyloid fibril forming hexa-peptides whose crystal structures are available in the Protein Data Bank (PDB) and (v) Experimentally validated aggregation prone regions found in amyloidogenic proteins. Furthermore, CPAD is linked to other related databases and resources, such as Uniprot, Protein Data Bank, PUBMED, GAP, TANGO, WALTZ etc. We have set up a web interface with different search and display options so that users have the ability to get the data in multiple ways. CPAD is freely available at http://www.iitm.ac.in/bioinfo/CPAD/. The potential applications of CPAD have also been discussed.

ɑ-Synuclein strains and the variable pathologies of synucleinopathies

Several decades ago, a mysterious transmissible agent was found responsible for a group of progressive and lethal encephalopathies affecting the nervous system of both animals and humans. This infectious agent showed a strain-encoded manner of inheritance even though it lacked nucleic acids. The identification of infectious proteins resolved this apparent conundrum. Misfolded infectious protein particles, or prions, were found to exist as conformational isomers with a unique fingerprint that can be faithfully passaged to next generations. Protein-based strain-encoded inheritance is characterized by strain-specific infectivity and symptomatology. It is found in diverse organisms, such as yeast, fungi, and mammals. Now, this concept is revisited to examine the pathological role of amyloid proteins involved in neurodegenerative diseases where it might underlie certain types of dementia and motor-related neurodegenerative disorders. Given the discovery of the SNCA gene and the identification of its gene product, ɑ-synuclein (ɑ-SYN), as the main histopathological component of Parkinson's disease, dementia with Lewy bodies and multiple system atrophy, the scientific community was left puzzled by the fact that a single protein appeared to be involved in different diseases with diverging clinical phenotypes. Recent studies are now indicating that ɑ-SYN may act in a way similar to prions and that ɑ-SYN misfolded structural variants may behave as strains with distinct biochemical and functional properties inducing specific phenotypic traits, which might finally provide an explanation for the clinical heterogeneity observed between Parkinson's disease, MSA, and dementia with Lewy bodies patients. These crucial new findings may pave the way for unexplored therapeutic avenues and identification of new potential biomarkers. Parkinson's disease and other synucleinopathies share ɑ-synuclein deposits as a common histopathological hallmark. New and ongoing developments are now showing that variations in the aggregation process and the formation of ɑ-synuclein strains may be paralleled by the development of distinct synucleinopathies. Here, we review the recent developments and the role of strains in synucleinopathies. This article is part of a special issue on Parkinson disease.

Comparison of the aggregation of homologous β2-microglobulin variants reveals protein solubility as a key determinant of amyloid formation

The mouse and human β2-microglobulin protein orthologs are 70% identical in sequence and share 88% sequence similarity. These proteins are predicted by various algorithms to have similar aggregation and amyloid propensities. However, whilst human β2m (hβ2m) forms amyloid-like fibrils in denaturing conditions (e.g. pH2.5) in the absence of NaCl, mouse β2m (mβ2m) requires the addition of 0.3M NaCl to cause fibrillation. Here, the factors which give rise to this difference in amyloid propensity are investigated. We utilise structural and mutational analyses, fibril growth kinetics and solubility measurements under a range of pH and salt conditions, to determine why these two proteins have different amyloid propensities. The results show that, although other factors influence the fibril growth kinetics, a striking difference in the solubility of the proteins is a key determinant of the different amyloidogenicity of hβ2m and mβ2m. The relationship between protein solubility and lag time of amyloid formation is not captured by current aggregation or amyloid prediction algorithms, indicating a need to better understand the role of solubility on the lag time of amyloid formation. The results demonstrate the key contribution of protein solubility in determining amyloid propensity and lag time of amyloid formation, highlighting how small differences in protein sequence can have dramatic effects on amyloid formation.

Protein aggregation, structural disorder and RNA-binding ability: a new approach for physico-chemical and gene ontology classification of multiple datasets

Background

Comparison between multiple protein datasets requires the choice of an appropriate reference system and a number of variables to describe their differences. Here we introduce an innovative approach to discriminate multiple protein datasets (multiCM) and to measure enrichments in gene ontology terms (cleverGO) using semantic similarities.

Results

We illustrate the powerfulness of our approach by investigating the links between RNA-binding ability and other protein features, such as structural disorder and aggregation, in S. cerevisiae, C. elegans, M. musculus and H. sapiens. Our results are in striking agreement with available experimental evidence and unravel features that are key to understand the mechanisms regulating cellular homeostasis.

Conclusions

In an intuitive way, multiCM and cleverGO provide accurate classifications of physico-chemical features and annotations of biological processes, molecular functions and cellular components, which is extremely useful for the discovery and characterization of new trends in protein datasets. The multiCM and cleverGO can be freely accessed on the Web at http://www.tartaglialab.com/cs_multi/submission and http://www.tartaglialab.com/GO_analyser/universal. Each of the pages contains links to the corresponding documentation and tutorial.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-2280-z) contains supplementary material, which is available to authorized users.

Distinct clinical and neuropathological features of G51D SNCA mutation cases compared with SNCA duplication and H50Q mutation

BACKGROUND

We and others have described the neurodegenerative disorder caused by G51D SNCA mutation which shares characteristics of Parkinson's disease (PD) and multiple system atrophy (MSA). The objective of this investigation was to extend the description of the clinical and neuropathological hallmarks of G51D mutant SNCA-associated disease by the study of two additional cases from a further G51D SNCA kindred and to compare the features of this group with a SNCA duplication case and a H50Q SNCA mutation case.

RESULTS

All three G51D patients were clinically characterised by parkinsonism, dementia, visual hallucinations, autonomic dysfunction and pyramidal signs with variable age at disease onset and levodopa response. The H50Q SNCA mutation case had a clinical picture that mimicked late-onset idiopathic PD with a good and sustained levodopa response. The SNCA duplication case presented with a clinical phenotype of frontotemporal dementia with marked behavioural changes, pyramidal signs, postural hypotension and transiently levodopa responsive parkinsonism. Detailed post-mortem neuropathological analysis was performed in all cases. All three G51D cases had abundant α-synuclein pathology with characteristics of both PD and MSA. These included widespread cortical and subcortical neuronal α-synuclein inclusions together with small numbers of inclusions resembling glial cytoplasmic inclusions (GCIs) in oligodendrocytes. In contrast the H50Q and SNCA duplication cases, had α-synuclein pathology resembling idiopathic PD without GCIs. Phosphorylated α-synuclein was present in all inclusions types in G51D cases but was more restricted in SNCA duplication and H50Q mutation. Inclusions were also immunoreactive for the 5G4 antibody indicating their highly aggregated and likely fibrillar state.

CONCLUSIONS

Our characterisation of the clinical and neuropathological features of the present small series of G51D SNCA mutation cases should aid the recognition of this clinico-pathological entity. The neuropathological features of these cases consistently share characteristics of PD and MSA and are distinct from PD patients carrying the H50Q or SNCA duplication.

From the baker to the bedside: yeast models of Parkinson's disease

The baker’s yeast Saccharomyces cerevisiae has been extensively explored for our understanding of fundamental cell biology processes highly conserved in the eukaryotic kingdom. In this context, they have proven invaluable in the study of complex mechanisms such as those involved in a variety of human disorders. Here, we first provide a brief historical perspective on the emergence of yeast as an experimental model and on how the field evolved to exploit the potential of the model for tackling the intricacies of various human diseases. In particular, we focus on existing yeast models of the molecular underpinnings of Parkinson’s disease (PD), focusing primarily on the central role of protein quality control systems. Finally, we compile and discuss the major discoveries derived from these studies, highlighting their far-reaching impact on the elucidation of PD-associated mechanisms as well as in the identification of candidate therapeutic targets and compounds with therapeutic potential.