Dataset Information

Prediction of amyloid aggregation in vivo.

ABSTRACT: Many human diseases owe their pathology, to some degree, to the erroneous conversion of proteins from their soluble state into fibrillar, β-structured aggregates, often referred to as amyloid fibrils. Neurodegenerative diseases, such as Alzheimer and spongiform encephalopathies, as well as type 2 diabetes and both localized and systemic amyloidosis, are among the conditions that are associated with the formation of amyloid fibrils. Several mathematical tools can rationalize and even predict important parameters of amyloid fibril formation. It is not clear, however, whether such algorithms have predictive powers for in vivo systems, in which protein aggregation is affected by the presence of other biological factors. In this review, we briefly describe the existing algorithms and use them to predict the effects of mutations on the aggregation of specific proteins, for which in vivo experimental data are available. The comparison between the theoretical predictions and the experimental data obtained in vivo is shown for each algorithm and experimental data set, and statistically significant correlations are found in most cases.

SUBMITTER: Belli M

PROVIDER: S-EPMC3128957 | biostudies-literature | 2011 Jul

REPOSITORIES: biostudies-literature

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Prediction of amyloid aggregation in vivo.

Belli Mattia M Ramazzotti Matteo M Chiti Fabrizio F

EMBO reports 20110701 7

Many human diseases owe their pathology, to some degree, to the erroneous conversion of proteins from their soluble state into fibrillar, β-structured aggregates, often referred to as amyloid fibrils. Neurodegenerative diseases, such as Alzheimer and spongiform encephalopathies, as well as type 2 diabetes and both localized and systemic amyloidosis, are among the conditions that are associated with the formation of amyloid fibrils. Several mathematical tools can rationalize and even predict impo ...[more]

PMID: 21681200

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Project description:Aging is the most important risk factor for neurodegenerative diseases associated with pathological protein aggregation such as Alzheimer's disease. Although aging is an important player, it remains unknown which molecular changes are relevant for disease initiation. Recently, it has become apparent that widespread protein aggregation is a common feature of aging. Indeed, several studies demonstrate that 100s of proteins become highly insoluble with age, in the absence of obvious disease processes. Yet it remains unclear how these misfolded proteins aggregating with age affect neurodegenerative diseases. Importantly, several of these aggregation-prone proteins are found as minor components in disease-associated hallmark aggregates such as amyloid-β plaques or neurofibrillary tangles. This co-localization raises the possibility that age-dependent protein aggregation directly contributes to pathological aggregation. Here, we show for the first time that highly insoluble proteins from aged Caenorhabditis elegans or aged mouse brains, but not from young individuals, can initiate amyloid-β aggregation in vitro. We tested the seeding potential at four different ages across the adult lifespan of C. elegans. Significantly, protein aggregates formed during the early stages of aging did not act as seeds for amyloid-β aggregation. Instead, we found that changes in protein aggregation occurring during middle-age initiated amyloid-β aggregation. Mass spectrometry analysis revealed several late-aggregating proteins that were previously identified as minor components of amyloid-β plaques and neurofibrillary tangles such as 14-3-3, Ubiquitin-like modifier-activating enzyme 1 and Lamin A/C, highlighting these as strong candidates for cross-seeding. Overall, we demonstrate that widespread protein misfolding and aggregation with age could be critical for the initiation of pathogenesis, and thus should be targeted by therapeutic strategies to alleviate neurodegenerative diseases.

Dataset Information

Prediction of amyloid aggregation in vivo.

Publications

Prediction of amyloid aggregation in vivo.

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