Abstract
BackgroundImpaired proteostatic regulation of proteins with prion-like domains (PrLDs) is associated with a variety of human diseases including neurodegenerative disorders, myopathies, and certain forms of cancer. For many of these disorders, current models suggest a prion-like molecular mechanism of disease, whereby proteins aggregate and spread to neighboring cells in an infectious manner. The development of prion prediction algorithms has facilitated the large-scale identification of PrLDs among “reference” proteomes for various organisms. However, the degree to which intraspecies protein sequence diversity influences predicted prion propensity has not been systematically examined.ResultsHere, we explore protein sequence variation introduced at genetic, post-transcriptional, and post-translational levels, and its influence on predicted aggregation propensity for human PrLDs. We find that sequence variation is relatively common among PrLDs and in some cases can result in relatively large differences in predicted prion propensity. Sequence variation introduced at the post-transcriptional level (via alternative splicing) also commonly affects predicted aggregation propensity, often by direct inclusion or exclusion of a PrLD. Finally, analysis of a database of sequence variants associated with human disease reveals a number of mutations within PrLDs that are predicted to increase prion propensity.ConclusionsOur analyses expand the list of candidate human PrLDs, quantitatively estimate the effects of sequence variation on the aggregation propensity of PrLDs, and suggest the involvement of prion-like mechanisms in additional human diseases.
Highlights
Impaired proteostatic regulation of proteins with prion-like domains (PrLDs) is associated with a variety of human diseases including neurodegenerative disorders, myopathies, and certain forms of cancer
In addition to proteins previously linked to prion-like disorders, we identify a number of high-scoring PrLD candidates whose predicted aggregation propensity increases for certain isoforms or upon mutation, and some of these candidates are associated with prion-like behavior in vivo yet are not currently classified as “prion-like”
Sequence variation in human PrLDs leads to wide ranges in estimated aggregation propensity Multiple prion prediction algorithms have been applied to specific reference proteomes to identify human PrLDs [8, 13, 38,39,40,41]
Summary
Impaired proteostatic regulation of proteins with prion-like domains (PrLDs) is associated with a variety of human diseases including neurodegenerative disorders, myopathies, and certain forms of cancer For many of these disorders, current models suggest a prion-like molecular mechanism of disease, whereby proteins aggregate and spread to neighboring cells in an infectious manner. The amino acid composition of these domains (rather than primary sequence) is the predominant feature conferring prion activity [5, 6] This observation has contributed to the development of a variety of composition-centric prion prediction algorithms designed to identify and score proteins based on sequence information alone [7,8,9,10,11,12,13]
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